Business Intelligence Scientist ADS Jobs in Bengaluru

Data Engineering Lead Bengaluru | Engineering | Full-Time About Fam (formerly FamPay) Fam is India s first payments app designed for everyone aged 11 and above. FamApp enables seamless online and offline payments through UPI and FamCard. Our mission is to empower over **250 million young Indians** to start their financial journey early, becoming financially aware and confident. Founded in 2019 by IIT Roorkee alumni, Fam is backed by top-tier investors including Elevation Capital, Y-Combinator, Peak XV (Sequoia Capital India), Venture Highway, and angels like Kunal Shah and Amrish Rao. About the Role We re looking for a visionary **Data Engineering Lead** to take **end-to-end ownership** of Fam s data ecosystem from data ingestion and storage to processing and delivering actionable insights. You ll **define the data strategy and architecture** that supports both batch and **real-time** use cases, ensuring scalability, reliability, and governance across the organization. You will be instrumental in enabling accurate, complete, and trusted data flow that powers business intelligence, analytics, and product decision-making. This role involves **leadership, strategic thinking**, and hands-on problem solving. What You ll Do Own the full data lifecycle: ingestion, organization, storage, processing, and presentation. Define and execute **data architecture and strategy** aligned with operational and analytical goals. Build **scalable, reliable, and observable data systems** supporting batch and near real-time processing. Ensure **data quality, governance, and compliance**, proactively resolving discrepancies. Collaborate with product, engineering, and business teams to define, track, and optimize key metrics. Anticipate data-related challenges and implement preventive solutions. Lead, mentor, and grow the data engineering team, fostering innovation and accountability. Must-Haves 10+ years experience in data engineering, including proven leadership of teams or projects. Expertise designing, building, and scaling end-to-end data pipelines and systems. Deep understanding of the data lifecycle, from ingestion through business reporting. Strong communication skills and ability to collaborate across technical and business teams. Solid knowledge of **data governance, quality assurance, and compliance standards**. Experience with observability and proactive monitoring for data systems. Proficiency in Python and SQL; familiarity with Scala or Java. Hands-on experience with streaming and batch data frameworks. Experience designing large-scale data lakes and warehouses with best practices for schema evolution and partitioning. Strong background with **cloud platforms (AWS, GCP, or Azure)**. Fintech or regulated industry experience is a plus. Good to Have Fintech-specific data experience, including regulatory compliance and reporting. Deployment experience with **real-time analytics** and event-driven architectures. Familiarity with containerization and infrastructure tools like Docker, Kubernetes, Terraform. Knowledge of data observability tools (Monte Carlo, Databand, etc.). Exposure to **ML pipelines** and model deployment. Solve challenging problems at the intersection of big data, real-time processing, and fintech. Lead impactful data initiatives at a rapidly growing startup. Collaborate with a world-class team of engineers, data scientists, and product leaders. Competitive compensation, equity, and benefits. Clear career growth opportunities in leadership and innovation. Perks That Go Beyond the Paycheck Relocation assistance for a smooth move. Free office meals (lunch & dinner). Generous leave policies (birthday, period, parental support, and more). Salary advances and loan policies for financial support. Quarterly rewards, recognition, and referral incentives. Access to the latest gadgets and tools. Comprehensive health insurance with mental health support. Tax benefits like food coupons, phone allowances, and leasing options. Retirement benefits including PF contribution, leave encashment, and gratuity. About FamApp FamApp focuses on financial inclusion for the next generation by offering UPI and card payments to users aged 11+. Our flagship product, FamX, integrates UPI and card payments seamlessly, helping users manage, save, and learn about their finances effortlessly. With over **10 million users**, FamApp is revolutionizing how young Indians transact eliminating the need to carry cash and offering customizable FamX cards with personal doodles for a fun, unique payment experience. Join Our Dynamic Team At Fam, we foster a people-first culture with flexible work schedules, generous leave, comprehensive health benefits, and mental health support. You ll be part of a passionate, talented, and fun team shaping the future of fintech for India s youth.

Staff Software Engineer AI & Automation Location: Bengaluru Company: Okta, The World s Identity Company Experience: 8+ Years Type: Full-Time About Okta Okta is the world s leading identity platform. We empower people to securely access any technology, anywhere, on any device. With products like the Okta Platform and Auth0, we place identity at the core of business security, enabling growth through safe digital transformation. At Okta, we value diverse perspectives and experiences. We believe in learning, collaboration, and building an inclusive environment where everyone belongs. About the Team The Business Technology - Shared Services team is at the forefront of Okta s internal digital transformation. We focus on building intelligent, automated platforms that simplify operations and deliver smarter, faster experiences to both employees and customers. We collaborate across engineering, data science, security, and business units to deliver cutting-edge solutions powered by Generative AI (GenAI), virtual agents, workflow orchestration, and intelligent recommendations. The Opportunity As a Staff Software Engineer, you ll play a critical role in designing and developing AI-powered platforms that drive automation, scale, and intelligence across Okta s business. You ll help make LLM-powered solutions and intelligent automation a reality for the enterprise ensuring performance, security, and reliability at scale. This is a hands-on, individual contributor (IC) role, ideal for engineers who are passionate about solving complex problems, architecting scalable systems, and pushing the boundaries of AI integration. What You ll Do Design & Build: Develop scalable backend services that embed GenAI and automation into core business workflows (e.g., virtual agents, document intelligence, smart routing). Collaborate Across Teams: Work closely with product managers, data scientists, and other engineers from ideation to production. Architect for Scale: Make key architectural decisions around LLM integration, API design, data flow, and observability. Code with Excellence: Write clean, secure, and maintainable code in Python, Java, or similar languages. Build for Production: Use Docker, Kubernetes, and CI/CD pipelines to build and deploy high-availability services. Champion Best Practices: Promote high standards for testing, security, code reviews, and operational readiness. Mentor & Guide: Support a collaborative team culture through peer mentorship and design reviews. What You ll Bring 8+ years of experience in software engineering with a strong track record of building and maintaining production-grade, cloud-native services. Expertise in distributed systems, API development, and cloud infrastructure (AWS, GCP, or Azure). Proficiency in Python, Java, or Go. Experience with Docker, Kubernetes, and observability tools (e.g., Prometheus, Grafana, ELK). Exposure to AI/ML concepts and eagerness to work with LLMs, NLP, or automation platforms. A strong sense of ownership, collaborative mindset, and a bias toward action. Passion for learning and working with emerging technologies especially in the AI and automation space. Why Join Okta Make AI Real: Help move GenAI from experimentation to enterprise-wide impact. Build with Purpose: Work on challenges that simplify and secure Okta s internal operations. Grow in a Human-Centered Culture: Join a humble, technically driven team that values learning, excellence, and personal growth. Join Okta and shape how identity, AI, and automation come together to power the modern enterprise.

Data Scientist I Job Type: Full-Time Category: Data Science Location: Bangalore About Bright Money Bright is a mission-driven consumer fintech company helping Americans get out of debt and build stronger financial futures powered by data science and machine learning. Our mobile platform provides personalized tools for credit building, debt paydown, budgeting, and loan refinancing. With 300,000+ users, 100,000+ reviews, and support from top-tier investors like Sequoia, Falcon Edge, and Hummingbird, Bright is one of the fastest-growing fintech startups in the U.S. We ve raised $90M+ in equity and debt funding to date. We're proud to be building a global-first, data-driven consumer tech company from India, for the world. About the Role As a Data Scientist I, you will be part of a high-impact team using data and machine learning to power Bright s core financial products. You ll work on problems that directly improve users financial outcomes modeling behavior, predicting intent, and enabling smarter, automated experiences. This is a hands-on role for someone with strong fundamentals in ML, statistics, and programming, and a desire to turn data into real-world product impact. Key Responsibilities Design and build predictive models using core concepts of machine learning, statistics, and probability. Analyze large-scale user and transactional data to extract insights and inform strategy. Collaborate cross-functionally with product managers, engineers, and business stakeholders to define and solve problems. Deploy ML models into production environments, ensuring scalability, stability, and performance. Tune, evaluate, and interpret model results to maximize business value and user outcomes. Document methodologies and workflows for reproducibility and team collaboration. Stay current with AI/ML advancements and experiment with new techniques as appropriate. Required Qualifications Bachelor s or Master s degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Strong grasp of ML and statistical concepts (e.g., regression, classification, hypothesis testing, probability distributions). Proficiency in Python or R, and experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch. Familiarity with model deployment tools and frameworks (e.g., Docker, Flask/FastAPI, MLflow). Understanding of how to implement and monitor models in a real-world production environment. Awareness of modern AI techniques including transformers, LLMs, and generative AI. Strong problem-solving skills, curiosity, and ability to communicate complex ideas clearly. Exposure to cloud platforms like AWS, GCP, or Azure is a plus. Bonus Points For Experience with deep learning and advanced neural network architectures. Understanding of MLOps best practices (CI/CD for ML, monitoring, retraining pipelines). Personal projects, open-source contributions, or research publications in AI/ML. What You ll Work On Model user behavior and financial patterns to power intelligent product features. Analyze complex transaction datasets to surface actionable insights. Build and deploy ML systems that personalize savings and debt management strategies. Apply deep learning, reinforcement learning, and LLMs to real-world fintech use cases. Collaborate with engineering and product teams to launch data-powered experiences in the Bright app. Experiment with cutting-edge AI technologies to innovate in consumer finance. At Bright, you ll go beyond theory you ll use data to change lives. This is your chance to build meaningful, scalable machine learning systems that empower users to take control of their financial future. Qualification : Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or a related quantitative field

Job Title: Sr. Data Science Engineer Location: Bangalore Experience: 5 8+ Years Job Description As a Senior Data Science Engineer, you will develop and maintain scalable data pipelines and manage API integrations to support growing data volume and complexity. You will play a key role in ensuring data quality and enabling accurate AI model development through effective data handling and automation. Responsibilities Monitor data quality and implement processes for data cleansing and validation. Analyze data to troubleshoot and resolve data-related issues promptly. Develop automation workflows for efficient data labeling, preparation, and augmentation to improve AI model accuracy and utility. Requirements Proven experience as a Data Scientist, Data Analyst, or related role, with experience in data mining. Strong proficiency in data manipulation using Python or R; familiarity with Scala, Java, or C++ for raw data processing is a plus. Experience with business intelligence tools (e.g., Tableau) and big data frameworks like Hadoop and Spark. Strong mathematical foundation, especially in statistics and algebra. Advanced SQL skills with experience in database development, data migration, and integration. Expertise in exploratory data analysis and familiarity with common data science toolkits. Ability to communicate complex data insights clearly and effectively to non-technical stakeholders. Familiarity with data management tools and experience applying machine learning and AI techniques.

Position: Data Scientist (AI/ML Expert) Location: Pritech Park SEZ, Block 09, 4th Floor B Wing, Survey No. 51 to 64/4, Outer Ring Road, Bellandur V, Bangalore, Karnataka, India Department: Advanced Analytics Employment Type: Subexian Experience Required: 1 to 3 years Job Overview: We are looking for a talented Data Scientist with expertise in AI/ML to join our Advanced Analytics team. As a key contributor, you ll design, develop, and validate predictive models, recommendation systems, and forecasting solutions, while also collaborating with cross-functional teams to deliver cutting-edge solutions using the latest technologies. Key Responsibilities: Model Development: Design, develop, and validate predictive models, recommendation systems, and forecasting solutions using a mix of statistical, machine learning, and deep learning techniques. You will work both independently and as part of a collaborative team. Data Visualization & Reporting: Communicate actionable insights effectively through compelling dashboards, reports, and visualizations using tools such as Superset, Power BI, and Python libraries (Matplotlib, Seaborn, Plotly). AI & Tech Solutions: Collaborate with teams to design and deliver flexible, scalable solutions using advanced technologies such as AI and large language models (LLMs). API Development: Develop and integrate REST APIs and frameworks such as Flask or FastAPI for seamless deployment of machine learning models. Documentation: Maintain clear, comprehensive documentation for data workflows, model development, and analytical methodologies to ensure knowledge sharing and transparency across teams. Continuous Learning: Stay up-to-date with the latest trends and advancements in data science, algorithms, and technologies, ensuring your skills and knowledge remain cutting-edge. Required Technical Skills: Python Proficiency: Strong experience with Python and libraries like Scikit-learn, TensorFlow/PyTorch, and data visualization libraries (Matplotlib, Seaborn, Plotly). SQL: Solid hands-on experience in SQL for efficient data querying. ML Ops & Pipelines: Understanding of machine learning operations (ML Ops) and ML pipelines for streamlined model deployment. Cloud & Distributed Computing: Exposure to cloud platforms such as AWS, Azure, or GCP and distributed computing tools like Hadoop, Spark, or Pyspark is a plus. Soft Skills: Effective Communication: Strong ability to communicate complex analytical findings in a clear and engaging manner, tailoring insights for both technical and non-technical audiences. Problem-Solving: A proactive problem-solver with the ability to adapt and thrive in a fast-paced, dynamic environment. Continuous Growth: Self-motivated, curious, and always seeking opportunities for professional growth and learning. At Subex, we encourage a collaborative, innovative, and growth-driven work environment. If you're passionate about applying data science techniques to real-world challenges and want to work with cutting-edge AI/ML technologies, we d love to hear from you!

Position: Data Science Intern Analytics, Automation & Problem Solving Location: Bangalore On-site Duration: 3 6 months Internship Experience: Final-year students or recent graduates About the Role: We re seeking a high-agency intern passionate about data and obsessed with solving real-world problems. At 5C Network, data goes beyond analysis it drives systems, operations, and healthcare outcomes. Join our Data Science & Analytics team to go beyond dashboards: own challenges, build automations, and work with data impacting thousands of lives. What You ll Work On: Complex Querying & Data Handling: Write and optimize high-performance SQL queries on large healthcare datasets (PostgreSQL, ClickHouse), troubleshoot discrepancies, and ensure data reliability. Python-based Data Transformation: Clean, manipulate, and transform raw data using Pandas and NumPy; contribute to backend scripts powering dashboards and reports. Dashboarding & Reporting: Assist in creating intuitive dashboards (Metabase, Power BI, Google Data Studio) used for operational, product, and clinical decision-making. Automations & Workflows: Identify repetitive tasks and automate processes with Python, APIs, and reporting tools. Advanced Applications: Collaborate on projects involving natural language data, smart assistants, and auto-triggered insights to enhance decision-making intelligence. Business Context Awareness: Understand the purpose behind every metric focus on solving impactful business problems, not just queries. What We Expect from You: Strong command of SQL with skills in query optimization, debugging, and managing complex data logic. Solid Python skills for data tasks (Pandas, NumPy, scripting). Comfort working with real-world messy data, databases, and schemas. Curiosity and initiative: Investigate anomalies rather than ignoring them. Business-first mindset: Always question the meaning behind metrics. High ownership: Proactively explore, propose solutions, and take charge without waiting for perfect instructions. Willingness to learn and stretch whether automating reports, building tools, or mastering new skills daily. Nice to Have: Experience with APIs, backend data workflows, or FastAPI. Familiarity with Git and data visualization platforms. Interest in healthcare or operations-heavy environments. Exposure to LLMs, text analytics, or no-code/low-code tools (even exploratory). Why This Internship is Different: Real projects with real impact on national healthcare delivery. Exposure to full-stack analytics from pipelines to dashboards to business strategy. Mentorship from experienced data scientists and engineers. Potential opportunity for full-time conversion based on performance. Perks: Paid internship with a stipend. Certificate of completion and potential pre-placement offer. Office located in Bangalore s vibrant startup and health-tech hub.

Job Title: Senior Data Scientist Location: Bangalore, Karnataka, India Department: DAC Experience: 4 to 6 years About the Role As a Senior Data Scientist, you will leverage your expertise in statistics, machine learning, and data analysis to extract meaningful insights from both structured and unstructured data. Working closely with cross-functional teams, you will develop predictive models, optimize business processes, and contribute significantly to data-driven decision-making across the organization. Key Responsibilities Translate complex business problems into testable hypotheses and proofs of concept, guiding the data science team towards delivery. Apply business acumen to analyze data and extract actionable insights. Communicate complex technical ideas effectively to stakeholders with varying levels of technical expertise. Employ a range of analytical and machine learning techniques to solve business challenges. Conduct research and develop innovative solutions to data analytics problems. Manage data collection, integration, analysis, and presentation across different business contexts. Adhere to and promote best software development practices including version control, peer reviews, and refactoring. Create and maintain thorough documentation of experiments and solutions, following frameworks like CRISP-DM. Stay updated with the latest data science trends, tools, and best practices, sharing knowledge with the team. Conduct peer code reviews and mentor junior data scientists. Drive improvements in data science delivery processes and champion their adoption within the team. Required Skills Technical: Advanced programming skills in Python and SQL. Strong foundation in Probability, Statistics, and hypothesis testing. Expertise in practical machine learning, including common pitfalls and mitigation strategies. Proficient with data visualization tools such as Tableau, PowerBI, and Python libraries (seaborn, matplotlib). Experience with modern development tools and collaborative coding practices. Intermediate cloud technology knowledge with experience deploying data science solutions on cloud platforms. Non-Technical: Pragmatic decision-making balancing solution perfection with business impact and timelines. Project planning and task delegation for data science teams. Ability to present complex insights to non-technical audiences via storyboarding and presentations. Strong written communication skills for technical documentation and paper submissions. Leadership and mentorship capabilities within the data science community. Preferred Skills (Good to Have) Advanced expertise in specialized areas such as Operations Research, NLP, Deep Learning, Time Series Forecasting, Reinforcement Learning, Graph ML, or Explainable AI. Advanced cloud technology knowledge, including application deployment. Ability to decompose business problems into technical subproblems matched with appropriate methodologies. Qualifications Bachelor s degree in Engineering, Technology, or a related technical field. 4 to 6 years of relevant data science experience. Work on impactful, cutting-edge AI and analytics projects with Fortune 500 clients. Collaborate with a passionate team of data scientists and engineers. Grow your technical and leadership skills in a fast-paced, innovation-driven environment. Qualification : Bachelors degree in Engineering, Technology, or a related technical field.

Job Title: AI/ML Architect Location: Bangalore, India Experience: 15 17 Years Employment Type: Full-Time Overview: We are seeking an experienced AI/ML Architect with 15 17 years of overall experience, including 2 3 years in project management. This strategic role requires deep expertise in AI/ML technologies, enterprise AI architecture, and hands-on delivery of cutting-edge solutions such as autonomous AI agents and generative AI platforms. The architect will lead the design, proposal, and execution of AI-driven solutions across diverse client engagements. Key Responsibilities: Solution Architecture & Design: Design and evolve robust AI/ML architectures incorporating autonomous agents, scalable business intelligence, and generative AI. Collaborate with cross-functional teams (data scientists, ML engineers, UX designers, and business strategists) to convert business needs into technical designs. Evaluate emerging technologies, frameworks, and trends to guide architectural roadmaps and innovation strategies. RFP Response & Proposal Development: Lead the technical response for RFPs, creating solution frameworks that align with client objectives and industry standards. Draft detailed technical proposals, use cases, and presentations to demonstrate the business value and ROI of AI solutions. Partner with sales and business teams to align proposals with market needs and positioning. Project Delivery & Technical Leadership: Oversee full AI/ML solution lifecycles from architecture design to deployment and monitoring ensuring compliance, quality, and performance. Provide hands-on guidance and mentorship to technical teams, promoting best practices in data science, ML model development, and deployment pipelines. Manage project schedules, resource planning, and risk mitigation for successful delivery outcomes. Stakeholder & Cross-Functional Collaboration: Act as the primary technical liaison across teams, ensuring stakeholder alignment on vision, progress, and technical challenges. Conduct technical workshops, reviews, and solution demos to showcase innovation and architectural decisions. Innovation & Continuous Improvement: Monitor industry trends, publications, and competitor offerings to integrate innovative features into AI/ML initiatives. Continuously refine and optimize existing platforms, ensuring scalability, performance, and user-centricity. Required Skills & Qualifications: 15 17 years of overall experience with 2 3 years in a leadership/project management role. Strong track record in AI/ML architecture, especially with autonomous agent systems, enterprise AI, and generative AI technologies. Proficient in modern AI/ML frameworks (TensorFlow, PyTorch, etc.), data pipelines, and cloud platforms (AWS, Azure, GCP). Experience designing and implementing end-to-end AI solutions in complex, data-driven environments. Demonstrated success in crafting technical proposals and responding to RFPs. In-depth knowledge of NLP, deep learning, traditional ML, and AI product integration. Effective project and stakeholder management skills; able to balance priorities across multiple projects. Excellent communication and presentation skills, with the ability to articulate AI value to technical and non-technical stakeholders.

Job Title: Lead Data Scientist Location: Bangalore North, Karnataka, India Job Type: Full-Time Industry: Entertainment / Mobile Gaming About Us We are one of India s most exciting and fast-growing mobile gaming companies. Founded in 2014 and partnered with Modern Times Group (MTG), our vision is to create simple, impactful casual game experiences at massive scale. Our portfolio includes evergreen hits such as Daily Themed Crossword, WordTrip, WordJam, WordWars, WordTrek, TileMatch, and Jigsaw. We have built a global network of chart-topping games supported by powerful tech and analytics infrastructure that fuels rapid growth. Position Summary As a Lead Data Scientist in our Central Analytics team, you will play a critical role in shaping data-driven strategies that enhance player experience and business performance. This fast-paced role offers abundant opportunities to work alongside product leaders and game teams, transforming complex data into actionable insights that drive user acquisition, engagement, and monetization. Key Responsibilities Collaborate closely with product leaders to provide data-driven advisory on strategic decisions. Partner with game development teams to analyze gameplay data and generate actionable insights that improve user acquisition, engagement, and monetization. Perform advanced exploratory data analyses and ad-hoc reporting to identify trends, issues, and opportunities across our game portfolio. Design, execute, and lead data research projects, delivering practical recommendations based on rigorous statistical analyses. Drive continuous improvement in game performance through innovative machine learning models and analytics techniques. Requirements Bachelor s/Master s/PhD degree in Computer Science, Statistics, or a related field. Proven experience with machine learning, statistical modeling, and data science projects. Hands-on proficiency in Python and/or Spark for data manipulation, visualization, and building ML models. Strong SQL skills with experience querying large, complex datasets from data lakes or warehouses. Demonstrated ability to lead research projects and translate findings into actionable business recommendations. Excellent interpersonal skills and a collaborative approach to working with cross-functional teams. Knowledge of Deep Learning frameworks and techniques is highly desirable. Work with a top-tier gaming company known for its innovative and data-driven culture. Influence millions of users worldwide through impactful analytics. Collaborate with talented teams in a high-growth, dynamic environment. Access to cutting-edge tools and technologies for data science and machine learning. Competitive compensation and career growth opportunities. Qualification : Bachelors/Masters/PhD degree in Computer Science, Statistics, or a related field.

Job Title: Senior Manager Data Science, Data Modelling & Analytics Location: Bengaluru Department: Insights & Analysis About the Role: As a Senior Manager, you will lead a team of data scientists and analysts, driving the development and deployment of advanced analytics solutions that enable data-driven decision-making. This role blends strategic leadership with hands-on technical expertise, playing a critical part in delivering impactful insights and analytics across the organization. Key Responsibilities: Hands-On Technical Contribution: Design, develop, and deploy advanced machine learning models and statistical analyses to address complex business challenges. Utilize Python, R, SQL, and other tools to manipulate data and build predictive models. Manage end-to-end data pipelines including collection, cleaning, transformation, and visualization. Collaborate with IT and data engineering teams to integrate analytics solutions into production environments. Provide thought leadership on analytics solutions and metrics aligned with business needs. Team Leadership & Development: Lead, mentor, and manage a team of data scientists and analysts, fostering collaboration and innovation. Guide career development, conduct performance evaluations, and promote skill enhancement. Encourage continuous learning and adoption of best practices in data science methodologies. Strategic Planning & Execution: Collaborate with senior leadership to define and execute data science strategy aligned with business goals. Identify and prioritize high-impact analytics projects that deliver business value. Ensure timely and quality delivery of analytics solutions balancing scope and resources. Client Engagement & Stakeholder Management: Act as primary point of contact for clients, translating business challenges into data science solutions. Lead client presentations, workshops, and discussions, effectively communicating complex analytical concepts. Build and maintain strong client relationships, managing expectations and deliverables. Deliver regular reports and dashboards to senior management and stakeholders. Bridge communication between technical teams and business units to align analytics initiatives with organizational objectives. Cross-Functional Collaboration: Work closely with Business Intelligence, Market Analytics, and Data Engineering teams to integrate analytics into business processes. Translate complex insights into actionable recommendations for non-technical stakeholders. Facilitate data-driven workshops and presentations across the organization. Collaborate with support functions to provide timely leadership updates on operational metrics. Governance & Compliance: Ensure compliance with data governance policies and data privacy regulations (e.g., GDPR, PDPA). Implement best practices for data quality, security, and ethical analytics use. Stay abreast of industry trends and regulatory changes affecting data analytics. Qualifications: Education: Bachelor s or Master s degree in Data Science, Computer Science, Statistics, Mathematics, or related field. Experience: 12+ years in advanced analytics, data science, data modelling, machine learning, or related fields. 5+ years in leadership roles managing analytics teams and projects. Experience in BFSI, Hi-Tech, Retail, or Healthcare industries preferred. Experience with media data is a plus. Technical Skills: Proficiency in Python, R, SQL. Experience with data visualization tools like Tableau, Power BI. Familiarity with big data platforms (Hadoop, Spark) and cloud services (AWS, GCP, Azure). Strong knowledge of machine learning frameworks and libraries. Soft Skills: Excellent analytical and problem-solving skills. Strong communication and interpersonal abilities. Ability to influence and drive organizational change. Strategic thinker focused on business outcomes. Desirable Expertise: Advanced Analytics Techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression, time series forecasting, classification, market mix modelling. Prescriptive Analytics: Optimization, simulation modelling. Text Analytics: NLP, sentiment analysis. Machine Learning Techniques: Supervised Learning: Linear/logistic regression, decision trees, random forests, gradient boosting, SVMs. Unsupervised Learning: Clustering, PCA, anomaly detection. Reinforcement Learning: Q-learning, deep Q-networks. Generative AI & Large Language Models (Good to Have): Experience with GPT, Gemini, LLAMA, etc. for text generation, summarization, conversational agents. Hyperparameter tuning, prompt engineering, embeddings, fine-tuning. Additional Skills: Proficiency with Tableau or Power BI (advanced visualization). Strong data management, structuring, and harmonization skills.

Position Title: Senior Data Engineer Databricks, PySpark, Cloud Platforms Location: Bengaluru Bellandur (GTP) Employment Type: Full-time Job Summary Synechron is looking for a Senior Data Engineer to join our advanced analytics team in Bengaluru. In this role, you will architect and build scalable, high-performance data pipelines that power data science, analytics, and business intelligence initiatives. You ll work with modern tools including Databricks, PySpark, and cloud data platforms, while collaborating across teams to ensure high-quality, secure, and efficient data solutions. Key Responsibilities Design, develop, and maintain large-scale, secure, and efficient data pipelines using Databricks, PySpark, and cloud-native tools. Partner with data scientists, analysts, and business stakeholders to translate requirements into robust data solutions. Integrate data from various structured, semi-structured, and streaming sources. Ensure high standards for data quality, performance optimization, security, and cost efficiency. Drive data pipeline automation, orchestration, and monitoring using tools like Airflow. Lead troubleshooting efforts, performance tuning, and enhancements of existing pipelines. Stay informed about emerging data technologies and recommend adoption where relevant. Technical Skills Core Expertise Programming: Python (expert), SQL (advanced), PySpark. Platforms: Databricks (clusters, notebooks, workflows), AWS/Azure/GCP. Data Orchestration: Apache Airflow (or similar). Data Warehousing: Snowflake (preferred), data modeling, ETL/ELT pipelines. Streaming: Kafka or other stream processing tools. DevOps: CI/CD (GitLab CI, Jenkins), version control (Git), containerization (Docker/Kubernetes preferred). Security: Familiarity with encryption, access controls, and compliance best practices. Experience 8+ years of experience in data engineering or related roles. Proven expertise in developing and deploying scalable data pipelines using Databricks, PySpark, and SQL. Hands-on experience with cloud platforms (AWS, Azure, or GCP). Strong background in data warehousing, especially with Snowflake. Exposure to real-time data processing and orchestration tools. Experience implementing CI/CD pipelines for data workflows is a plus. Daily Responsibilities Build and optimize data ingestion, transformation, and storage workflows. Collaborate with cross-functional teams to align data solutions with business objectives. Monitor, troubleshoot, and continuously improve pipeline performance. Conduct data quality checks, ensure governance and compliance standards. Contribute to technical documentation, code reviews, and team knowledge sharing. Qualifications Bachelor s or Master s degree in Computer Science, IT, or related field. Relevant certifications (e.g., Databricks Certified Data Engineer, AWS Certified Data Analytics) are preferred. Professional Competencies Strong problem-solving and analytical mindset. Effective communicator with ability to collaborate across technical and non-technical teams. Time management and prioritization skills under tight deadlines. Proactive leadership and a passion for innovation. Commitment to ethical data use and data security. Diversity & Inclusion at Synechron Synechron is committed to building an inclusive, diverse, and equitable workplace. Through our global Same Difference DEI initiative, we celebrate and support people from all backgrounds, including race, gender, sexual orientation, religion, age, disability, and more. We offer flexible work arrangements, continuous learning, internal mobility, and mentoring programs to support every employee s growth. Qualification : Bachelors or Masters degree in Computer Science, IT, or related field

Subject Matter Expert (SME) Production Optimization Location: Bengaluru Department: Global Strategic Services Data Science EMEA Employment Type: Full-Time | Hybrid About Cognite Cognite is a global SaaS leader driving industrial digital transformation through AI and data. Our flagship solutions include Cognite Atlas AI and Cognite Data Fusion (CDF), empowering industries such as Oil & Gas, Chemicals, Pharma, Manufacturing, and Energy to optimize operations and innovate at scale. We have been honored with awards like the 2022 Technology Innovation Leader and 2024 Microsoft Energy and Resources Partner of the Year. Our Values Impact: Deliver meaningful results in every endeavor. Ownership: Take responsibility beyond boundaries, fostering inclusivity and teamwork. Relentless: Innovate persistently with resilience and care. Role Overview As a Production Optimization SME, you will leverage deep industry expertise to guide Cognite s Data Science and Customer Success teams in delivering data-driven production optimization solutions. Acting as a trusted advisor, you will collaborate with project teams and customers to ensure maximum value realization through strategic and technical guidance. Key Responsibilities Advise customers and internal teams on production optimization challenges and solutions. Collaborate with Project Managers, Customer Success, Sales, and Product teams to align delivery with business goals. Translate customer needs into actionable project scopes and solution designs. Demonstrate the value of Cognite Data Fusion and related applications for production optimization. Create demos, visualizations, and supporting materials for customer implementations. Provide on-site technical support and mentoring to technical teams, especially data scientists. Gather and relay customer feedback to improve products and solutions. Stay current on industry trends, Big Data, Business Intelligence, and Machine Learning technologies. What You Bring Bachelor s degree in Petroleum Engineering, Chemical Engineering, or related technical field. 5+ years experience in production engineering with expertise in: Optimizing production near wellbore, completions, and pipeline/network systems Designing and troubleshooting artificial lift systems (ESP, gas-lift, sucker rod pumps) Using multiphase flow simulators (Prosper, Gap, Pipesim) Analyzing reservoir and well performance data Conducting flow assurance studies (corrosion, scale, wax, hydrates, slugs) Familiarity with data-driven production optimization challenges and technologies. Python programming skills are a plus. Excellent presentation, coaching, and communication skills across organizational levels. Self-motivated, results-driven, and able to work independently and collaboratively. Proficient in English. Join a diverse, global team representing 70+ nationalities, with a strong focus on Diversity, Equality, and Inclusion (DEI). Work from a modern hybrid office environment in Bengaluru (Rathi Legacy, Hoodi). Enjoy a flat organization with direct access to leadership and minimal bureaucracy. Collaborate on ambitious projects impacting multiple industries worldwide. Engage with the Cognite HUB to exchange ideas and connect with peers and partners. Make Your Impact Be part of Cognite s mission to power digital transformation with DataOps and AI, enabling industrial clients to optimize operations sustainably and make better decisions every day. We welcome candidates from all backgrounds apply today! Qualification : Bachelors degree in Petroleum Engineering, Chemical Engineering, or related technical field.

Data Scientist Experience: 5+ Years Location: Bangalore, Karnataka, India Job Type: Full Time Job Summary We are seeking an experienced Data Scientist with over 5 years of expertise to join our innovative team in Bangalore. The ideal candidate will have hands-on experience in advanced statistical methods, machine learning, and deep learning frameworks, combined with strong skills in deploying models at scale. Key Responsibilities Apply advanced Statistics and Operations Research methods to solve complex business problems. Develop and deploy predictive and machine learning models using frameworks such as PyTorch, TensorFlow, Keras, and XGBoost. Utilize data engineering and big data tools including PySpark, Databricks, and Flask for building scalable data solutions. Implement and fine-tune NLP models like RNN, LSTM, and attention-based architectures, leveraging pre-trained models from Stanford, IBM, Azure, and OpenAI. Design and optimize efficient SQL queries to extract data from large databases. Work with visualization tools like D3.js, Dash Plotly, and deploy interactive dashboards using Streamlit. Utilize graph databases such as Neo4j for complex data relationships. Manage version control with tools like GitHub or Bitbucket. Deploy machine learning models into production environments using MLOps practices on cloud platforms such as AWS or Azure. Required Skills 5+ years of professional experience as a Data Scientist or similar role. Strong foundation in statistics, machine learning, and deep learning techniques. Proficient in Python-based data science libraries and frameworks. Hands-on experience with cloud-based MLOps and deployment. Excellent SQL skills for data extraction and manipulation. Experience with version control systems and collaborative development. Familiarity with NLP techniques and modern pre-trained language models. Strong problem-solving and communication skills. Qualifications Any graduate degree in Computer Science, Statistics, Mathematics, Engineering, or related field. Join a forward-thinking company in Bangalore, where you will work with cutting-edge technologies to create impactful data-driven solutions. Grow your career in an environment that values innovation, diversity, and continuous learning.

Senior Data Scientist Location: Bangalore, Karnataka, India Department: DAC Experience Required: 4 6 Years Education: B.E./B.Tech or equivalent Open Positions: 10 About the Role This is an exciting opportunity to apply your technical expertise while mentoring junior data scientists, influencing technical strategies, and ensuring the highest quality of data-driven decision-making. Key Responsibilities Data Science & Analytics Translate business problems into testable hypotheses and develop proofs of concept. Build and deploy predictive models and machine learning solutions using Python, SQL, and cloud platforms. Use advanced statistical techniques, data mining, and visualization to derive insights from structured and unstructured data. Collaborate with stakeholders to deliver actionable insights and ensure analytical solutions are effectively communicated to both technical and non-technical audiences. Design experiments, conduct hypothesis testing, and create data-driven narratives to support decision-making. Technical Leadership Guide and mentor junior data scientists on best practices, project design, and technical execution. Conduct code reviews, ensure quality documentation, and uphold software development standards (version control, refactoring, collaborative coding). Share emerging trends and best practices in the field to foster team-wide learning. Actively participate in peer learning, technical sessions, and team knowledge-sharing. Project Management Break down complex data science projects into smaller tasks, assign responsibilities, and monitor execution. Balance business impact with execution timelines to deliver pragmatic solutions over theoretical perfection. Create and maintain documentation using standardized frameworks (e.g., CRISP-DM). Required Skills Technical (Must-Have) Advanced proficiency in Python and SQL. Expertise in Probability & Statistics, hypothesis testing, and predictive modeling. Solid hands-on experience with Machine Learning (regression, classification, clustering, etc.). Strong data visualization skills with tools like Tableau, Power BI, and libraries such as matplotlib, seaborn. Experience with cloud platforms (Azure, AWS, or GCP) and modern development tools. Non-Technical (Must-Have) Strong communication skills: Ability to present technical findings to non-technical stakeholders. Project planning, risk management, and delivery tracking experience. Leadership qualities: Mentorship, peer collaboration, and driving process improvements. Excellent written communication for documenting scientific approaches and writing whitepapers. Preferred Skills (Good to Have) Advanced Technical Skills Expertise in areas like NLP, Deep Learning, Reinforcement Learning, Graph ML, or Time Series Forecasting. Hands-on deployment experience using MLOps tools and advanced cloud-native services. Solutioning Acumen Ability to break down complex business challenges and match them with the most effective technical solutions. What Makes You a Great Fit You are a problem solver with a deep understanding of machine learning applications. You thrive in a collaborative environment and excel at mentoring others while growing your own skills. You are motivated by impact and have the ability to translate raw data into strategic insights. Perks & Benefits Opportunity to work on cutting-edge, enterprise-scale problems. Be a part of a collaborative, intellectually curious team. Mentorship and career development support. Access to advanced tools, resources, and cloud technologies.

Principal Data Scientist / Data Science Manager Ads Team Location: Bangalore, Karnataka | Department: Tech Shape the Future of AdTech at Meesho Join Meesho s high-impact Data Science team often compared to the Avengers for our ability to solve some of the toughest data problems in India s e-commerce landscape. We build intelligent, scalable systems that serve millions of users across diverse product categories. Our work in fraud detection, inventory optimization, and platform vernacularization continues to unlock new possibilities in digital commerce. Now, as part of our Ads team, we re seeking a visionary Principal Data Scientist / Data Science Manager to elevate our advertising technology through cutting-edge machine learning solutions. About the Role As a leader within our AdTech division, you ll design, implement, and scale innovative ML solutions for real-time bidding, ad ranking optimization, budget pacing, and performance measurement. Your work will drive business impact and help define the future of our monetization strategy. Key Responsibilities Design and develop advanced bidding and budget pacing algorithms to optimize ad spend and ROI Create experimental frameworks to measure ad effectiveness and attribution Collaborate cross-functionally to transform business needs into efficient AI/ML-based solutions Define and communicate the long-term data science roadmap with business and tech leadership Mentor junior data scientists and guide team-level strategy Lead research initiatives in ML, auction theory, and AdTech domains Required Qualifications B.Tech in Computer Science, Machine Learning, or related field with 6+ years of hands-on experience Strong expertise in auction theory, predictive modeling, causal inference, and reinforcement learning Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow Experience with big data tools and environments Proven ability to mentor teams and manage complex analytical projects Excellent written and verbal communication skills Preferred Qualifications M.Tech or Ph.D. in Computer Science or related discipline with ML specialization 3+ years of experience working in AdTech, real-time bidding systems, or programmatic advertising Track record of taking ML research to production Publications in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, AAAI) About Meesho Meesho is India s top-rated e-commerce workplace and the first Indian horizontal e-commerce platform. We empower over 1.75 million sellers and serve customers across every serviceable pincode in India. Our platform enables small businesses and entrepreneurs to thrive online by offering zero commission, lowest shipping cost, and state-of-the-art logistics support. We combine local relevance with a strong technology backbone to deliver a uniquely inclusive shopping experience. Our Mission Democratizing Internet Commerce for Everyone We aim to enable 100 million small businesses to sell online. Our seller-first approach, innovation-first culture, and focus on the underserved population of Bharat drive everything we do. Our Culture & Benefits At Meesho, we ve built a people-first, high-performance culture backed by 11 guiding principles (our "Mantras"). Our employees benefit from a workplace that encourages reflection, continuous growth, and mobility. What We Offer: Competitive compensation including equity options and performance bonuses Comprehensive wellness support via our MeeCare Program medical, mental, and financial wellbeing Flexible benefits, including generous leave policies, parental support, and L&D assistance Support with relocation, telehealth, fitness, and recreational discounts Frequent engagement activities, performance recognition, and a fun, inclusive environment If you are ready to lead transformative projects in advertising and machine learning at scale, apply today and help us redefine commerce in India. Apply now and join Meesho s Data Science revolution. Qualification : B.Tech in Computer Science, Machine Learning, or related field with 6+ years of hands-on experience

Machine Learning Engineer Full-Time - Bengaluru, India - Data Science / Artificial Intelligence / Engineering Join our dynamic Data Science / Artificial Intelligence / Engineering team in Bengaluru, India as a Full-Time Machine Learning Engineer and play a key role in driving data-driven innovation! We are seeking a skilled and results-oriented Machine Learning Engineer to design, build, and deploy scalable machine learning models that address real-world business challenges. You will collaborate closely with data scientists, engineers, and product managers to transform raw data into actionable insights and integrate intelligent features into our products. As a Machine Learning Engineer, you will be responsible for the complete lifecycle of machine learning models and pipelines, from design and development to seamless deployment for a variety of applications. This includes classification, regression, clustering, recommendation systems, and time-series forecasting. You will leverage your expertise to preprocess and analyze large and complex datasets, extracting meaningful features and valuable insights. Collaboration with cross-functional teams will be crucial as you identify strategic ML opportunities and define clear success metrics. A key aspect of this role involves optimizing machine learning models for peak performance, scalability, and accuracy within production environments. You will build robust APIs or efficient microservices to integrate these models seamlessly into our applications, utilizing tools such as Flask or FastAPI. Continuous improvement is paramount, and you will be responsible for the ongoing monitoring and retraining of models based on their performance and any signs of data drift. Staying at the forefront of the field is essential, and you will be expected to stay updated with the latest ML research and emerging technologies, applying them to continuously enhance our product capabilities. Key Responsibilities: Design, develop, and deploy machine learning models and pipelines for diverse applications including classification, regression, clustering, recommendation, and time-series forecasting. Preprocess and analyze large datasets to extract meaningful features and actionable insights. Collaborate effectively with cross-functional teams to identify strategic ML opportunities and define clear success metrics. Optimize models for maximum performance, scalability, and accuracy in production environments. Build robust APIs or efficient microservices to integrate ML models into applications using tools like Flask or FastAPI. Continuously monitor and retrain models based on performance metrics and potential data drift. Stay updated with the latest ML research and technologies and apply them to enhance product capabilities. Minimum Qualifications: Bachelor s or Master s degree in Computer Science, Data Science, Statistics, or a related field. 2+ years of proven experience as a Machine Learning Engineer or in a similar role. Strong proficiency in Python and key ML libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch. Practical experience working with both SQL and NoSQL databases. Solid knowledge of essential data preprocessing, effective feature engineering, and robust model evaluation techniques. Familiarity with standard software engineering practices, including version control (Git), thorough code reviews, and efficient CI/CD pipelines. Preferred Qualifications: Prior experience with deep learning, natural language processing (NLP), or computer vision. Familiarity with major cloud services like AWS, GCP, or Azure (especially SageMaker, Vertex AI, etc.). Understanding of modern MLOps tools and practices (e.g., MLflow, Kubeflow, DVC). Practical experience with containerization and orchestration tools (Docker, Kubernetes). Knowledge of big data tools (e.g., Spark, Hadoop) is considered a significant plus. What We Offer: Competitive salary and performance-based incentives to reward your contributions. Comprehensive health insurance and valuable wellness benefits to support your well-being. Dedicated learning and development programs for continuous professional growth. Exciting opportunities to work on impactful, real-world AI/ML projects with significant scale. A collaborative, inclusive, and innovative work culture that fosters teamwork and creativity. Flexible working hours and a hybrid work model to promote a healthy work-life balance.

Chief Analytics Office (CAO) - Data Scientist Location: Bangalore, Karnataka, India Job Type: Full-Time Experience Level: 2-4 years Company: IBM Chief Analytics Office (CAO) Introduction: At IBM, we believe in the power of AI and data science to transform enterprises. In the Chief Analytics Office (CAO), we work on the front lines of AI-driven enterprise transformations. By joining our team, you will collaborate with innovative leaders and contribute to solving complex problems using the latest AI and machine learning technologies. Here, your skills will not only be valued but nurtured in a dynamic, collaborative environment designed for growth and impact. Role Overview: As a Data Scientist within IBM's Chief Analytics Office, you will play a critical role in driving AI and data science initiatives across the enterprise. You will use your technical expertise to develop and deploy machine learning models and data analytics solutions that align with business objectives. This role is focused on translating data insights into actionable recommendations and leading data science projects from concept to execution. Key Responsibilities: Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Assist in the implementation and optimization of AI-driven strategies aligned with business stakeholder requirements. Refine data-driven methodologies for enterprise transformation projects. Data Science and AI: Design, implement, and optimize machine learning solutions and statistical models. Perform end-to-end data analysis, from problem formulation through to deployment. Ensure the scalability of AI solutions by leveraging cloud platforms. Apply IBM s data science standards and reusable assets to ensure quality and consistency. Project Support: Lead and contribute across various stages of AI and data science projects, from data exploration to model development and deployment. Monitor project timelines and assist in resolving any technical challenges. Design and implement measurement frameworks to assess the business impact of AI solutions using KPIs. Collaboration: Work closely with stakeholders to ensure alignment with strategic goals. Collaborate with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Provide technical expertise to cross-functional teams, fostering a collaborative environment. Required Education and Experience: Education: Bachelor s or Master s degree in Computer Science, Data Science, Statistics, or a related field. An advanced degree is strongly preferred. Experience: 2-4 years of experience in data science, AI, or analytics, with a focus on implementing data-driven solutions. Experience with data cleaning, data analysis, A/B testing, and data visualization. Hands-on experience with AI technologies through coursework or projects. Required Technical Skills: Programming and Data Analysis: Proficiency in SQL and Python for data analysis and developing machine learning models. Familiarity with machine learning algorithms such as linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks (e.g., TensorFlow, PyTorch). Cloud Platforms & Data Processing: Experience with cloud-based platforms (e.g., AWS, Azure, IBM Cloud) and data processing frameworks. Specialized Knowledge: Knowledge of large language models (LLMs) and familiarity with IBM s WatsonX product suite. Familiarity with object-oriented programming (OOP) principles. Analytical and Soft Skills: Problem-Solving: Strong analytical skills with the ability to solve complex problems and derive actionable insights from datasets. Communication: Excellent communication skills to explain technical concepts clearly to stakeholders at various levels. Project Management: Ability to handle multiple initiatives simultaneously, prioritize effectively, and meet deadlines in a fast-paced environment. Preferred Experience: Advanced Degree: A Master s degree in a related field is strongly preferred. Impact: Work on innovative projects that directly impact enterprise transformation using the latest AI and data science techniques. Collaboration: Be part of a collaborative environment with a global team of AI experts. Growth: Develop professionally with continuous learning opportunities in the ever-evolving AI field. Work-Life Balance: IBM offers a dynamic work environment with flexibility and career growth opportunities. Apply now and join IBM's Chief Analytics Office as a Data Scientist and be part of the next generation of data-driven innovations. Qualification : A Masters degree in a related field is strongly preferred.

Job Title: Data Scientist Location: Bengaluru Experience: 4+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc offers a next-generation platform that delivers unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitability, empowering teams to deliver projects faster, smarter, and with greater control. Join us in shaping the future of construction tech. If you thrive in a dynamic, fast-growing environment and want to make a significant impact, Linarc is the place for you. This is a full-time position based in Bengaluru. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to address complex business problems. Build predictive models and algorithms to forecast customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover key insights and trends. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Design and optimize data pipelines for both real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to effectively communicate findings and business performance. Present actionable insights and recommendations to stakeholders and leadership teams. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes and optimize user experience. Research & Development: Stay updated with the latest developments in machine learning, artificial intelligence, and data science. Explore and implement new techniques and tools to drive innovative solutions and improve outcomes. Qualifications: Minimum Experience: 3 years of professional experience in Data Analytics, Data Science, AI, or Machine Learning. Technical Expertise: Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis of large datasets using tools like SQL, Hive, Spark, or similar. Proficiency in machine learning and deep learning tools such as Scikit-learn, TensorFlow, PyTorch, and familiarity with techniques like Neural Networks, Gradient Boosting, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, Clustering, etc. Experience working with visualization tools such as Tableau and Power BI. Business & Innovation: Demonstrated ability to innovate solutions and solve business problems using data science techniques. Desirable Additional Experience: 4+ years of experience in data science or machine learning in a product-focused environment. Experience working with relational or document databases. Proficiency in C, Python, PyTorch, Java, JavaScript, Node.js, React.js, or Vue.js. Strong knowledge of hypothesis testing and regression analysis. Experience in a SaaS product environment. Educational Qualifications: Bachelor s/Master s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

Data Scientist - Global Sugar and Ethanol Production Company Description: Louis Dreyfus Company is a leading merchant and processor of agricultural goods, active across the entire value chain from farm to fork. We operate a broad range of business lines, leveraging our global reach and extensive asset network to serve customers and consumers worldwide. As a matrix organization spanning six geographical regions and ten platforms, we are present in over 100 countries and employ approximately 18,000 people globally. Job Description: We are seeking an experienced Data Scientist to join our team, focusing on managing and analyzing global Sugar and Ethanol production data. This role involves integrating large datasets, applying statistical estimation methods, and developing interactive dashboards to support data-driven decision-making. You will work closely with cross-functional teams to generate insights that enhance business strategies and identify risks in production trends. Main Responsibilities: Manage and estimate global Sugar and Ethanol production and associated risks. Integrate large datasets from various sources and perform feature engineering to improve data quality and usability. Apply statistical methods and estimation techniques to analyze production trends and assess risks. Develop and maintain interactive dashboards to visualize key metrics and insights. Present findings and recommendations to stakeholders through detailed reports and presentations. Collaborate with cross-functional teams to ensure data-driven decision-making across the organization. Experience: Minimum of 3 years of experience in data science, preferably within the commodities sector. Advanced proficiency in Python programming, with expertise in libraries such as Pandas, NumPy, and Scikit-learn. Strong understanding of data integration and feature engineering techniques. Experience in statistical analysis and modeling. Proficiency in data visualization tools such as Dash. Excellent communication and presentation skills. Ability to work independently and as part of a team. Qualifications: Master s degree in economics, applied statistics, or a related field. A Ph.D. is a plus. Fluency in English, both oral and written. Experience working in a commodities-related field is preferred. Qualification : Masters degree in economics, applied statistics, or a related field. A Ph.D. is a plus.

Your Impact As a Data Science Analyst at McKinsey, you will collaborate closely with the Insights & Analytics (IA) group and consulting teams to solve analytically complex client problems in the marketing domain. You will apply advanced analytical and modeling techniques, drawing insights through statistical techniques and predictive modeling to guide marketing efforts. Your primary responsibility will be client service, with an additional focus on knowledge development within the team. Key activities will include: Performing statistical analysis and modeling to support marketing-related client engagements. Developing and refining statistical models aimed at optimizing pricing strategies and promotional activities. Providing guidance to teams on analytics projects, particularly on technique and modeling-related issues. Supporting the development and maintenance of McKinsey s proprietary marketing techniques and contributing to other knowledge development initiatives. Coaching and mentoring new hires by sharing your business, technical, and functional expertise. Delivering high-quality, client-ready end products on time, with attention to detail and performing quality checks as required. Your Growth You will be a key part of McKinsey s Growth, Marketing & Sales (GM&S) team, based in either Gurgaon or Bengaluru, primarily supporting the Insights & Analytics (IA) group of GM&S. This team leverages McKinsey's decades of experience in marketing and sales to help leading companies improve pricing, promotions, assortments, and performance management. The GM&S Solutions team blends cutting-edge software, tailored services, and deep expertise to provide clients with a comprehensive view of their commercial and financial performance. By integrating various data sources into a central data warehouse, the team enables clients to make informed decisions using advanced analytics. McKinsey Solutions fosters innovation in areas such as design thinking, mobile, and social, helping to reshape the consulting model toward asset-based solutions. This is a growing area within McKinsey, with a vibrant ecosystem of alliances, strategic acquisitions, and the development of new products and services that redefine how McKinsey works with clients. As part of McKinsey Solutions, you ll be part of a team of more than 1,000 dedicated professionals, including over 800 analysts and data scientists, working on impactful, innovative solutions. Your Qualifications and Skills Mandatory: Master s degree in Statistics, Economics, Econometrics, Computer Science, Engineering, Mathematics, or an MBA with a strong quantitative background. 2+ years of relevant work experience in analytics, business intelligence, or advanced analytics with an analytics firm. Proficiency in statistical programming software such as Python, and comfortable working with large datasets. Familiarity with R and SQL is also preferred. Experience in handling large volumes of data, including data manipulation, data cleansing, and data matching using tools like R, SQL, and Excel VBA. Strong analytical and problem-solving skills, with the ability to break down complex issues, identify root causes, and recommend actionable solutions. Knowledge of forecasting, regression analysis, and segmentation methodologies. Experience with modeling techniques, including logistic regression, linear regression, cluster analysis, CHAID, and similar approaches. Industry experience in consumer goods, telecom, or retail is a plus. Ability to thrive in a dynamic and evolving environment where priorities change frequently, and methodologies are often challenged. Capacity to work efficiently under pressure and meet tight deadlines. Qualification : Masters degree in Statistics, Economics, Econometrics, Computer Science, Engineering, Mathematics, or an MBA with a strong quantitative background.