Predictive Modeling Scientist ADS Jobs in Bengaluru

Position: Mechatronics & Big Data Scientist Developer Department: Research & Development Reporting To: General Manager Location: Bengaluru Key Responsibilities Machine Learning: Select features, build, and optimize classifiers using advanced machine learning techniques. Data Mining: Perform data mining using state-of-the-art methods to extract valuable insights from large datasets. Data Enhancement: Extend the company s datasets with third-party data sources when necessary to improve model accuracy and relevance. Data Collection & Processing: Improve data collection procedures to include all necessary information for building analytic systems. Data Cleansing & Integrity: Process, cleanse, and verify the integrity of data used for analysis to ensure reliable results. Ad-hoc Analysis: Perform ad-hoc analysis as needed, presenting the results in a clear, actionable manner. Anomaly Detection: Design and implement automated anomaly detection systems, tracking their performance over time to ensure accuracy. Behavioral Competencies Data-Driven: Strong inclination toward working with data and applying analytical thinking to solve complex problems. Detail-Oriented: Meticulous in data analysis and system development to ensure quality and precision in results. Skills and Expertise Machine Learning Algorithms Strong understanding of machine learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Data Science Tools Experience with common data science toolkits like R, Weka, NumPy, and MatLab. Proficiency in at least one (preferably NumPy or R) is highly desirable. Data Visualization Skilled in data visualization tools such as D3.js, GGplot, or similar. Database Management Experience with query languages such as SQL, Hive, Pig, NiFi, or others depending on the company s stack. Familiarity with NoSQL databases like InfluxDB, MongoDB, Cassandra, HBase. Statistical Analysis Strong applied statistics skills, including distributions, statistical testing, and regression analysis. Programming Skills Good scripting and programming skills in languages like PHP, Slim, SQL, and Laravel. Big Data Technologies Knowledge of Hadoop, HDFS, NiFi, and other big data platforms and technologies. Qualifications Essential: MTech, MS, or equivalent in Mechatronics, Computer Science, or a related field. Experience: Minimum 2 years of hands-on experience in developing SDKs and working with Big Data platforms. Proven track record in machine learning, data mining, and data science projects. Qualification : MTech, MS, or equivalent in Mechatronics, Computer Science, or a related field

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

Associate Credit Operations Job Type: Full-Time Category: Operations Location: Bangalore About Bright Bright is a consumer fintech company dedicated to helping Americans get out of debt using advanced data science and machine learning. Our mobile app integrates all the tools needed for managing and eliminating debt covering credit score building, automated debt paydown plans, financial and budget planning, and loan refinancing across credit cards, student loans, and car loans. With 300,000+ users, 6x growth in the last year, and over 100,000 ratings and reviews, Bright is one of the fastest-growing fintech platforms in the U.S. Supported by top venture capital firms like Sequoia, Falcon Edge, and Hummingbird, Bright has raised over $40 million in funding, including a recent $50M debt financing from Encina Lender Finance. Bright is ranked among the top 8 U.S. fintech companies and is poised to become a top-100 financial institution by leveraging data science and predictive modeling. We are proud to be building the first large-scale consumer tech company from India for global markets. About Our Founders Bright was founded in 2019 by industry veterans from McKinsey s Banking Practice and data scientists from InMobi: Petko Plachkov, Avi Patchava, Varun Modi, Avinash Ramakath, and Jayashree Merwade. Role Overview As an Associate Credit Operations professional, you will play a crucial role in assessing creditworthiness, supporting loan underwriting and approval, and ensuring smooth credit operations. You will work closely with cross-functional teams to monitor credit metrics, facilitate collections, and drive improvements in operational efficiency. Key Responsibilities Conduct thorough creditworthiness assessments following company policies and guidelines. Review customer profiles and credit applications against underwriting standards. Manage loan approval processes and support decision-making with sound judgment. Utilize collection systems to assist in managing delinquent accounts and dues recovery. Monitor and report on credit-related performance metrics regularly. Handle customer conflicts and disputes with a strong customer-centric approach. Investigate customer requests by gathering relevant data and exploring all information sources. Identify opportunities for process improvements to increase efficiency and effectiveness. Collaborate with teams to ensure compliance with credit policies and regulatory requirements. 1-2 years of experience in credit assessment, underwriting, or a related role. Strong understanding of credit product workflows and end-to-end process flows. Familiarity with credit risk assessment principles and banking domain knowledge. Knowledge of the U.S. credit environment and regulatory framework is a plus. Excellent verbal and written communication skills. High analytical and investigative capabilities. Ability to manage credit-related metrics and performance indicators. Strong negotiation, interpersonal skills, and ability to handle conflicts diplomatically. Join a fast-growing fintech startup backed by leading investors. Gain exposure to credit operations and risk management in a global context. Work alongside experienced professionals passionate about transforming consumer finance. Opportunity to grow within a dynamic, collaborative environment.

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!

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: 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.

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

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.

About the job At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. Responsibilities Interact cross-functionally with a variety of leaders and teams, and work with Engineers and Product Managers to identify opportunities for design and to assess improvements for advertising measurement products. Collaborate with teams to define questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, bidding etc., and develop and implement quantitative methods to answer those questions. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analyses that include data gathering and requirements specification, exploratory data analysis (EDA), model development, and delivery of results to business partners and executives. Build and prototype analysis pipelines iteratively to provide insights at scale. Develop knowledge of Google data structures,metrics, advocating for changes where needed for product development. Minimum qualifications: Master's degree in Statistics or Economics, a related field, or equivalent practical experience. 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. Experience with statistical data analysis such as linear models, multivariate analysis, causal inference, or sampling methods. Experience with statistical software (e.g., SQL, R, Python, MATLAB, pandas) and database languages along with Statistical Analysis, Modeling and Inference. Preferred qualifications: Experience translating analysis results into business recommendations. Experience understanding potential outcomes framework and with causal inference methods (e.g., split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators). Experience selecting tools to solve data analysis issues. Experience articulating business questions and using data to find a solution. Knowledge of structural econometric methods. Qualification : Master's degree in Statistics or Economics, a related field, or equivalent practical experience.

About the job Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. Account Management provide a secure and scalable platform that makes ad buying easier for businesses of all sizes. We take a strong Customer First mindset and have a responsibility to help advertisers achieve their business goals. Be a part of a team of analysts passionate about learning and using cutting edge data science and analytics techniques to shape our next generation Ads Account Management efforts. This role will manage a team of Data Scientists based out of Bengaluru. In this role, you will be responsible for managing a team and delivering insights, building and measuring key metrics, creating and maintaining reporting to assess our account management efforts. Responsibilities Work closely with the Account Management leadership team, UX, Marketing, and Support to develop a deep understanding of the needs of our advertisers, developers, and other partners. Set the direction, strategy, manage priorities and backlog of analytics projects, and coach a team of data scientists that support our account management efforts. Perform deep technical analyses with unstructured data (e.g., logs) to assess the success of our mobile efforts and new agency/large company account management products. Investigate fundamental business and product strategy questions. Deliver deep insights on specific topics and areas to provoke new feature/product ideas, or new interventions to drive improved advertiser experiences. Drive strategic analysis and reporting for business health metrics, focusing on retention, cost savings, and performance. Minimum qualifications: Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience. 7 years of experience with statistical data analysis, modeling, experimentation, causal inference, data mining, querying, and managing analytical projects with programming in SQL, Python, or R. 7 years of experience developing and managing metrics or evaluating programs/products. 5 years of experience as a people manager within a technical leadership role. Preferred qualifications: Experience managing a team of Data Scientists. Experience working with large and multiple datasets/data warehouses, and ability to pull from such data sets using relevant tools and coding. Strong business acumen and experience with utilizing unstructured data to answer open-ended business questions. Ability to start and direct work in an unstructured environment and comfortable dealing with ambiguity. Expertise in experimental design (e.g., A/B, multivariate, Bayesian methods) and incrementality analysis. Qualification : Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.

Position Purpose: At Bayer, we are committed to solving the world s most challenging problems, including revolutionizing farming practices. We are seeking a Data Scientist - Agronomy & Remote Sensing to lead the development of data-driven agricultural solutions. By combining expertise in soil science, crop modeling, remote sensing, and advanced analytics, you will create innovative digital products that enhance agricultural productivity and improve farming practices. Key Responsibilities Innovation & Experimentation: Collaborate with cross-functional teams to build data-driven solutions and offerings for farmers. Model Development: Develop weather and climate change models using statistical and process-based methods. Field Experiments: Design and lead field experiments, guiding field officers for data collection and model validation. Predictive Modeling: Build predictive models to map soil properties and field variabilities using statistical and modeling techniques. Collaboration: Work with data scientists and engineers to develop models that diagnose, predict, and analyze crop performance. Deployment: Deploy analysis results and models into customer-facing services, monitor performance, and improve models. Data Handling: Clean, analyze, and visualize complex agricultural, remote sensing, and geospatial datasets to derive actionable insights. Data Quality: Work with the data quality team to resolve any data-related issues. Who You Are Educational Qualification: MS with 5+ years of experience in soil research and remote sensing, or Ph.D. in Remote Sensing, Soil Science, Agronomy, Environmental Science, or a related field. Experience: Expertise in remote sensing, agricultural, and geospatial datasets, applying data science techniques to real-world problems. Strong background in soil hydrology and/or Agronomy with experience in using geospatial datasets (e.g., SoilGrids, ERA5). Proficiency in GIS software for geospatial analysis. Experience with Python/R and SQL for data analysis. Familiarity with statistical modeling techniques like Linear Regression, Partial Least Squares, Random Forest, Neural Networks, etc. Dynamic Shared Ownership (DSO): Bayer promotes a culture of productivity, innovation, and faster results, reshaping how we work together. Equal Opportunity Employer: Bayer values fairness, respect, and diversity, offering equal opportunities regardless of race, religion, gender, or other factors.

Job Title: AI/ML Engineer Location: Bangalore Experience: 4 5 Years Qualification: Bachelor s or Master s Degree in Computer Science or a related field Job Description Design and develop machine learning and deep learning systems tailored to business needs. Select and preprocess appropriate datasets; implement and optimize ML algorithms. Conduct machine learning experiments, run tests, and perform statistical analysis to fine-tune models. Train, retrain, and maintain ML systems to ensure accuracy and performance. Extend and customize existing ML libraries and frameworks. Stay updated with the latest research and advancements in machine learning and AI. Requirements Proven experience as a Machine Learning Engineer or similar role. Strong understanding of data structures, data modeling, and software architecture. Deep knowledge of mathematics, probability, statistics, and algorithms relevant to ML. Proficiency in writing clean, robust code in Python. Experience with ML frameworks such as TensorFlow or PyTorch, and libraries like scikit-learn. Skilled in deploying ML models and developing APIs for production environments. Experience with AWS cloud and ML services; knowledge of SageMaker is a plus. Qualification : Bachelors or Masters Degree in Computer Science or a related field

Position: Manager - Analytics Location: SEZ4, Bangalore, Karnataka, India Department: Advanced Analytics Employment Type: Subexian Experience Required: 6 to 9 years Job Overview: We are seeking an experienced Manager - Analytics to lead a team of talented data scientists in delivering impactful data-driven solutions. The ideal candidate will have a solid background in analytical methodologies, including machine learning, statistical modeling, and business analytics. You ll be responsible for collaborating with business stakeholders, driving the design and development of advanced analytics models, and ensuring the delivery of high-quality insights that support strategic decision-making. Key Responsibilities: Analytical Methodology: Research, evaluate, and implement new analytical methodologies and approaches to build innovative data-driven solutions. Utilize a blend of mathematics, statistics, machine learning, and business knowledge to solve complex problems. Business Collaboration: Work closely with business leaders and data owners to define key problems and challenges, ensuring the solutions developed have a significant impact on the business. Team Leadership: Lead and mentor a team of junior data scientists, guiding them through the development, deployment, and refinement of machine learning models in a production setting. Advanced Modeling: Utilize a wide range of analytical models, including reliability models, Markov models, stochastic models, Bayesian modeling, classification models, neural networks, and more to address business challenges effectively. Hands-On Expertise: Apply strong hands-on skills in R and Python, using libraries such as NLTK and Sklearn for developing machine learning models and data analysis. Large Data Management: Work with large datasets and distributed computing frameworks like MapReduce, Hadoop, and Hive, ensuring scalable and efficient data processing. Continuous Improvement: Stay up to date with the latest advancements in analytics and machine learning, continually enhancing models and methodologies to deliver cutting-edge insights. Required Technical Skills: Hands-on Experience in Python & R: Strong proficiency in R and Python programming, with experience in libraries such as NLTK, Sklearn, and other machine learning frameworks. Advanced Statistical & Machine Learning Techniques: Proven expertise in at least one of the following: Reliability models Markov Models Stochastic models Bayesian Modelling Classification Models Cluster Analysis Neural Networks NLP (Natural Language Processing) Deep Learning Non-parametric Methods Multivariate Statistics Big Data Tools: Experience working with large datasets and distributed computing platforms such as MapReduce, Hadoop, Hive, etc. Soft Skills: Leadership & Collaboration: Strong leadership skills with the ability to mentor a team of junior data scientists. Excellent collaboration and communication skills to work with business and technical teams. Problem-Solving & Critical Thinking: Ability to approach complex business problems analytically and come up with data-driven solutions. Continuous Learning: A passion for staying up to date with the latest trends and advancements in analytics, machine learning, and data science. At Subex, you ll have the opportunity to work on cutting-edge projects that make a tangible impact on the business. If you're passionate about leading analytics teams and leveraging data science to drive business success, we would love to have you on board.

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.

Data Scientist Location: Bengaluru Department: Global Strategic Services Data Science EMEA Type: Full-Time | Hybrid About Cognite Cognite is a global SaaS leader harnessing AI and data to solve complex business challenges across industries such as Oil & Gas, Chemicals, Pharma, Manufacturing, and Energy. Our flagship solutions include Cognite Atlas AI, an industrial agent workbench, and the Cognite Data Fusion (CDF) platform. Recognized as a 2022 Technology Innovation Leader and the 2024 Microsoft Energy and Resources Partner of the Year, Cognite is at the forefront of industrial digital transformation. Our Values Impact: We focus on meaningful results. Ownership: We take responsibility, foster inclusivity, and share success. Relentless: We pursue innovation with determination and resilience. Who You Are 3+ years of industry experience (or academic equivalent) in Oil & Gas, Manufacturing, or Power & Utilities, developing analytical solutions for production optimization, predictive maintenance, and related applications (e.g., well monitoring, event prediction, production planning). 1+ years serving as a domain expert on internal or customer projects. Proficient in Python and its data ecosystem (pandas, numpy), and ML libraries such as scikit-learn, Keras, etc. Skilled in data visualization tools like PowerBI, Grafana, Tableau, or web frameworks like Plotly Dash, Streamlit. Advocates for software best practices, including automated testing and documentation. Experienced with version control systems such as Git. Comfortable contributing to large-scale software projects. Pragmatic thinker able to balance short- and long-term tradeoffs. Trusted advisor on machine learning applications, with excellent communication skills for technical stakeholders and customers. Experienced mentor and quality assurer for junior team members. Cloud experience, including building streaming models and deploying serverless functions. Track record working across diverse industries. Eager to stay current with advances in generative AI and explore its practical applications for customers. Be part of a diverse global team with 70+ nationalities and a strong commitment to Diversity, Equality, and Inclusion (DEI). Work from our Bengaluru office (Rathi Legacy, Hoodi) in a modern hybrid environment. Benefit from a flat organizational structure with direct access to decision-makers. Collaborate on impactful, ambitious projects alongside talented professionals across industries. Engage with our community through internal HUBs and open conversations. Make an Impact Join Cognite and help transform industrial sectors by enabling better decisions through AI and data. We encourage candidates of all backgrounds to apply. If you re ready to grow and innovate with us, apply today!

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.

Lead Data Scientist Location: Bengaluru, India Employment Type: Full-time, Hybrid About Neuron7.ai Neuron7.ai is a rapidly growing AI-first SaaS company creating service intelligence products that are transforming industries such as high-tech devices, manufacturing, and medical devices. Backed by top Silicon Valley venture capitalists and an esteemed group of angel investors, we are recognized as a startup to watch. Our AI-driven platform helps enterprises make accurate service decisions at scale by delivering service predictions in seconds. By analyzing structured and unstructured data, alongside insights from leading experts, we empower service leaders to improve key metrics like first-call resolution, turnaround time, and service margins. At Neuron7.ai, you'll be part of a dynamic and innovative team that is redefining service intelligence. We value creativity, collaboration, and a commitment to pushing boundaries. Our goal is to lead the AI revolution in service decision-making, and we want you to be a part of that journey. About the Team As a Lead Data Scientist, you ll play a pivotal role in designing, developing, and deploying NLP-driven solutions for processing and analyzing large volumes of unstructured data. Your deep technical expertise will help launch AI products that directly impact users. You ll also mentor junior team members, ensuring technical excellence and fostering growth within the team. You'll collaborate closely with cross-functional teams and customers to solve complex challenges and create impactful AI solutions. What You ll Do: Lead NLP Development: Oversee the development and deployment of NLP-based solutions for processing and analyzing unstructured data at scale. Machine Learning Model Development: Design, train, and optimize machine learning models using popular libraries such as PyTorch, NLTK, and Scikit-learn. Cloud Deployment: Architect and deploy AI/ML products on cloud platforms such as Azure, GCP, or AWS. Collaboration: Work with data engineering teams to ensure seamless integration of AI models into production systems. Data Analytics: Perform advanced SQL analytics to extract actionable insights from structured datasets. Mentorship: Guide and mentor junior data scientists, fostering a culture of technical excellence within the team. Customer Engagement: Work closely with customers to understand their needs and translate those into technical solutions. Communicate complex technical concepts to non-technical stakeholders. Stay Current: Keep up-to-date with the latest advancements in NLP and machine learning to ensure best practices and cutting-edge solutions are applied. What We re Looking For: Experience: Minimum 10 years of experience in data science, specifically focused on NLP and unstructured data processing. Track Record: Proven experience in launching NLP-driven products to live users. Technical Expertise: Expertise in Python and libraries such as PyTorch, NLTK, and Scikit-learn. Hands-on experience with Transformer-based models (e.g., BERT, GPT). Cloud Proficiency: Strong experience with cloud platforms like Azure, GCP, or AWS for hosting and deploying AI/ML products. Data Engineering Knowledge: Familiarity with data engineering pipelines and best practices for scalable AI model deployment. SQL Proficiency: Proficient in SQL for data manipulation and advanced analytics. Problem-Solving: Excellent problem-solving skills with a strong ability to work with large-scale datasets. Leadership & Communication: Strong interpersonal and communication skills, with the ability to mentor team members and interact effectively with customers. Preferred Skills: MLOps Knowledge: Understanding of MLOps practices for model deployment, monitoring, and lifecycle management. Data Processing Tools: Familiarity with tools like Airflow, Spark, or similar frameworks for data processing. Customer-Facing Experience: Background in working with customer-facing applications and APIs to deliver AI-powered solutions. What We Do and Value: At Neuron7.ai, we prioritize integrity, innovation, and a customer-centric approach. Our mission is to enhance service decision-making using advanced AI technology, and we are committed to delivering excellence in all aspects of our work. Company Perks & Benefits: Competitive salary, equity, and spot bonuses Paid sick leave Latest MacBook Pro for your work Comprehensive health insurance Paid parental leave Hybrid work model with flexibility to work from our vibrant Bengaluru office Our Commitment to Diversity and Inclusion: Neuron7.ai is committed to fostering a diverse and inclusive workplace. We ensure equal employment opportunities without discrimination based on race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, marital status, or any other characteristic protected by law. If you re passionate about building innovative AI-driven solutions and want to be part of a forward-thinking team, we d love to hear from you!

Data Scientist with GenAI | Bengaluru, India About Wipro Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a global IT services and consulting company with over 230,000 employees in 65+ countries. We provide transformative digital solutions across consulting, engineering, and cloud. Job Overview We are seeking a skilled Data Scientist with Generative AI expertise to lead the development of AI/ML solutions using advanced technologies like LLMs, LangChain, and AWS. You will architect and implement end-to-end GenAI pipelines for enterprise-grade applications. Key Responsibilities Design and implement AI/ML solutions using Python and AWS. Develop GenAI systems using LLMs, LangChain, and RAG pipelines. Fine-tune AI models to optimize performance and accuracy. Create custom solutions when off-the-shelf tools don t meet requirements. Build SQL-based data pipelines extracting from Snowflake for model training. Integrate NLP capabilities into AI architecture to process textual data. Ensure responsible AI practices including security, fairness, and transparency. Lead and mentor team members, upholding coding and design standards. Communicate progress, risks, and strategies to stakeholders clearly. Mandatory Skills Python GenAI, LLMs AWS Cloud Services Preferred Skills NLP, AI/ML LangChain, RAG SQL, Snowflake Model fine-tuning and custom architecture development Join Wipro and be part of a global digital transformation journey. We empower talent to lead innovation and embrace reinvention. Applications from people with disabilities are explicitly encouraged.

Position: Senior Data Scientist Location: Bangalore Employment Type: Full-time Experience Required: 5 to 7 years Purpose of the Position: The Senior Data Scientist will play a key role in designing, developing, and implementing machine learning models and algorithms to solve complex business problems. The role involves collaborating with data scientists, software engineers, and business stakeholders to deliver scalable, efficient machine learning solutions that drive innovation and improve business outcomes. Key Responsibilities: Model Development and Optimization: Develop, train, and optimize machine learning models to meet business objectives. Ensure models are accurate, efficient, and scalable. Data Pipeline and Infrastructure: Design and maintain robust data pipelines to support machine learning workflows. Ensure data quality and integrity throughout the data lifecycle. Deployment and Monitoring: Deploy machine learning models into production. Monitor model performance and implement improvements as needed. Collaboration and Communication: Work with cross-functional teams to understand business requirements and translate them into technical solutions. Communicate complex technical concepts to non-technical stakeholders. Research and Innovation: Stay up to date with the latest advancements in machine learning and AI. Experiment with new techniques and technologies to enhance the organization's capabilities. Essential Skills: Machine Learning Frameworks: Experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Programming Languages: Strong skills in Python and R. Data Processing: Experience with tools like Pandas, NumPy, and Spark. Model Deployment: Experience with Docker, Kubernetes, MLflow, and FastAPI. Databases: Strong experience in databases like Snowflake, MongoDB, and Cosmo DB. Statistical Analysis: Strong foundation in statistics and probability. Model Management: Experience establishing model management, monitoring, support, and maintenance frameworks. ML Lifecycle: Experience setting up ML lifecycle processes and governance policies, as well as providing L0, L1, and L2 support. Desired Skills: Deep Learning: Familiarity with deep learning frameworks like TensorFlow or PyTorch. Natural Language Processing (NLP): Understanding of NLP techniques and applications. Cloud Computing: Experience with cloud platforms like AWS, Azure, or Google Cloud. Big Data Technologies: Knowledge of big data technologies such as Hive, Pig, or Cassandra. Software Engineering: Proficiency in software development and version control systems like Git. Qualifications: Education: Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field. Experience: Over 5 years of experience in machine learning, with a proven track record of developing and deploying models. Certifications: Relevant certifications in machine learning or data science are a plus. Key Qualities: Analytical Thinking: Strong analytical and problem-solving skills. Communication: Excellent verbal and written communication skills. Team Player: Ability to work effectively in a collaborative team environment. Adaptability: Flexibility to adapt to changing business needs and technologies. Innovation: A proactive approach to exploring new ideas and technologies. Apply now to join our dynamic team and lead innovation through machine learning and AI! Qualification : Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.