Scientist Jobs in Gurgaon

Senior Data Scientist | FinBox | Gurgaon Location: Gurgaon Experience: 6-8 Years About FinBox FinBox is a cutting-edge fintech company that is reshaping how financial services are provided to businesses and consumers. Since our launch in 2017, we ve developed some of the most innovative technologies in the financial services space, enabling lenders such as Banks, NBFCs, and large enterprises to create and launch credit products in just days. As a Series A-funded company, we are expanding globally with offices in India, Vietnam, Indonesia, and the Philippines. Our mission is to build the best-in-class infrastructure for lending products, helping financial services companies scale and launch credit programs that set new standards in the era of digital finance. We've helped our clients disburse billions of dollars in credit, covering a wide range of unsecured and secured products like personal loans, business loans, mortgages, and education loans. We ve made a significant impact, supporting over 100 companies and serving millions of customers every month. Why You Should Join FinBox: Innovative Environment: We foster a culture of creativity and experimentation, encouraging our team to push the boundaries of what s possible in fintech. Impactful Work: Your work will directly influence millions of lives by making credit more accessible to individuals and businesses. Growth Opportunities: As a Series A-funded startup, we offer numerous opportunities for professional development and career advancement. Collaborative Culture: Be part of a diverse, inclusive team of experts who are passionate about making a difference and supporting each other. Role Overview: As a Senior Data Scientist at FinBox, you will work at the intersection of data and business, helping to deliver impactful solutions in the lending space. You will be responsible for analyzing large datasets, extracting meaningful insights, and applying advanced data science techniques to improve products and drive business results. Key Responsibilities: Data Analysis & Insights Generation: Analyze big data to produce actionable insights that directly contribute to product improvements and business outcomes. Model Building & Experimentation: Develop and deploy algorithms to extract useful information from large datasets. Use statistical analysis and machine learning techniques to create predictive models. Data Visualization & Reporting: Create interactive dashboards and visualizations to help monitor key metrics and inform stakeholders. Automate report generation using data visualization tools. Collaborate with Teams: Work closely with business teams to translate customer requirements into problem definitions and develop algorithmic solutions to address business challenges. Data Processing & Pre-processing: Gather, clean, and preprocess relevant data for insight generation and model building. Present Complex Results: Distill complex analysis into simple, clear visualizations and explanations for stakeholders at all levels. Apply Data Science Techniques: Use techniques such as exploratory data analysis (EDA), regression analysis, decision trees, clustering, survival analysis, and more. Continuous Improvement: Apply iterative analytics to steer the continuous improvement of products and algorithms. Who You Are: Analytical Thinker: You have strong analytical skills and a passion for deriving actionable insights from complex data. Technical Proficiency: Proficient in Python, R, SQL, and Excel. Familiarity with AWS and Git is highly preferred. Data Science Knowledge: Solid understanding of statistical concepts, machine learning models, and algorithms. Knowledge of data science tools and techniques for large-scale data analysis. Data Visualization Expert: You can create clear and impactful visualizations to communicate findings effectively. Problem Solver: You thrive on tackling ambiguous problems and developing innovative solutions that directly impact the business. Collaborative: You enjoy working in a team environment and are able to translate technical concepts into business-friendly language for diverse audiences. Desired Qualifications: 6-8 years of experience in data science with a focus on machine learning and statistical modeling. Expertise in Python, R, SQL, and Excel for data analysis and visualization. Experience with AWS, Git, and other cloud-based technologies. Solid understanding of statistical concepts, machine learning algorithms, and model deployment. Experience with data visualization tools and creating dashboards. Ability to effectively communicate complex results to non-technical stakeholders. Innovative Culture: At FinBox, we love disruption and creativity. Here, you can take ownership and contribute ideas that directly impact our product and the industry. Global Impact: Work on high-impact projects with global customers, improving access to credit for millions. Career Growth: FinBox offers a fast-paced, dynamic environment where you can rapidly grow your career. Collaboration & Diversity: Join a team of talented, passionate people who value collaboration and diverse perspectives. If you re ready to make a real difference in fintech and enjoy solving complex problems with data science, apply now to be part of the FinBox team!

Principal Data Scientist | FinBox | Gurgaon Location: Gurgaon Experience: 8-11 Years About FinBox FinBox is at the forefront of transforming the financial services industry with our innovative technologies. Since our inception in 2017, we have empowered lenders, such as Banks, NBFCs, and large enterprises, to build and launch credit products quickly within days rather than months or years. As a Series A funded company, we re expanding globally with offices in India, Vietnam, Indonesia, and the Philippines. Our mission is to build world-class infrastructure for lending products, helping financial services companies scale and launch credit programs that set a new standard in digital finance. We've already helped our customers disburse billions of dollars in credit across unsecured and secured credit, including personal loans, working capital loans, business loans, mortgages, and education loans, impacting over 5 million customers every month. Why You Should Join FinBox: Innovative Environment: We cultivate creativity and experimentation. We want you to challenge the status quo and push boundaries in fintech. Impactful Work: Your contributions will have a direct, positive impact on millions of lives, making credit more accessible to individuals and businesses globally. Growth Opportunities: As a Series A-funded startup, FinBox provides tremendous opportunities for career development and professional growth. Collaborative Culture: Join a diverse, inclusive, and highly skilled team, all passionate about making a meaningful difference in the fintech world. Role Overview: As a Principal Data Scientist at FinBox, you will play a critical role in driving data science initiatives and shaping the direction of data-driven decision-making. You will leverage your deep expertise in machine learning and statistics to design and deploy predictive models, optimize algorithms, and lead experimentation processes that directly impact our products and business strategies. You will work closely with cross-functional teams to translate business requirements into data-driven solutions and collaborate on deploying models at scale. Key Responsibilities: Data Analytics & Insights: Analyze large, complex datasets to generate insights that drive business growth and measure the impact of business decisions. Model Development & Experimentation: Design, build, and deploy predictive models, using machine learning techniques such as regression, clustering, decision trees, and survival analysis. Algorithm Development: Optimize algorithms to process data efficiently, supporting better decision-making across the business. A/B Testing & Experimentation: Lead A/B testing and other experimentation methodologies to refine products and optimize business strategies. Data Visualization & Reporting: Create automated dashboards and reports using visualization tools like Tableau or Power BI to clearly communicate insights to stakeholders. End-to-End Data Processing: Manage the full lifecycle of data processing from gathering and cleaning data to creating models and deploying them in production. Stakeholder Collaboration: Collaborate with product, engineering, and business teams to translate business needs into data-driven solutions. Model Deployment: Ensure that machine learning models are effectively deployed at scale and optimized for real-time business applications. Who You Are: Experience: 8+ years of experience in data science, with a proven track record in the finance or fintech industry. Technical Expertise: Strong proficiency in Python, R, SQL, and Excel for data analysis, model development, and automation. Cloud & Version Control: Proficiency in AWS for cloud-based deployment and Git for version control. Advanced Data Science Skills: Expertise in statistical methods and machine learning techniques including regression, clustering, decision trees, bootstrapping, and survival analysis. Data Visualization: Extensive experience with data visualization tools like Tableau, Power BI, or open-source libraries (e.g., Matplotlib, Seaborn). Problem Solving & Communication: Strong problem-solving skills with the ability to distill complex models into actionable insights for business stakeholders. Deployment Experience: Experience in deploying and maintaining machine learning models at scale, focusing on automation, real-time analytics, and continuous improvement. Innovative Culture: Join a team that is dedicated to pushing the boundaries of what is possible in fintech, with an environment that fosters creativity and experimentation. Global Impact: Your work will directly influence the future of financial services, helping millions of customers access fair and accessible credit. Career Growth: As a growing startup, FinBox offers substantial opportunities for personal and professional growth. Collaborative Team: Work with a team of talented, driven professionals who believe in collaboration, inclusivity, and shared success.

Data Scientist | FinBox | Gurgaon Location: Gurgaon Experience: 3-6 Years About FinBox: Where Fintech Meets Fun! Welcome to FinBox, where technology, innovation, and creativity meet to revolutionize financial services. Since our inception in 2017, we've been on a mission to transform the lending industry by helping lenders like Banks, NBFCs, and enterprises launch credit products faster than ever before. As a Series A funded company, we are growing rapidly with offices in India, Vietnam, Indonesia, and the Philippines. Our vision is to build world-class infrastructure for lending products that help banks and financial services companies scale globally. We've already helped customers disburse billions of dollars in both unsecured and secured credit, and our solutions are used by over 100 companies, impacting over 5 million customers monthly. Innovative Environment: We encourage creativity and experimentation, pushing the boundaries of what's possible in fintech. Impactful Work: Your contributions will directly impact the lives of millions, making credit more accessible. Growth Opportunities: As a growing Series A startup, we offer ample opportunities for professional development. Collaborative Culture: Join a diverse and supportive team that values different perspectives. Creative Thinkers: We love people who challenge the norm and bring fresh, out-of-the-box ideas. Customer Heroes: We need those who understand customer needs and go above and beyond to deliver exceptional experiences. Team Players: If you thrive in a collaborative environment and believe in the power of "we," you'll fit right in. How You'll Contribute to Our Data Science Team: Analyze structured and unstructured data to derive meaningful insights. Support predictive model development and statistical analyses to guide product decisions. Build dashboards and visualizations to monitor and report key business metrics. Assist in data gathering, pre-processing, and cleaning to maintain high-quality datasets. Conduct exploratory data analysis and hypothesis testing to enable data-driven decision-making. Automate reports and develop clear, effective data visualizations. Document data processes and findings in a structured, presentable format. Collaborate with cross-functional teams to translate business needs into actionable data-driven solutions. Apply foundational machine learning techniques, including regression analysis, clustering, and decision trees. Who You Are: Experience: 3+ years in data science, analytics, or a related field. Technical Skills: Strong proficiency in Python/R, SQL, and Excel for data manipulation and analysis. Visualization: Experience with tools like Tableau, Power BI, or similar for data visualization. Additional Skills: Familiarity with AWS, Git, and version control practices is a plus. Knowledge: Understanding of statistical concepts and basic machine learning models. Mindset: Eagerness to learn, experiment, and grow in a fast-paced, dynamic startup environment.

Job Title: Associate Data Scientist - Social Media Analytics About this Role: Join Gartner s Social Media Analytics team, where you will help generate actionable insights from social media and internal/external Gartner data. This role is perfect for someone passionate about learning new technologies, text analytics, and working with unstructured data. As an Associate Data Scientist, you'll analyze data, draw recommendations, and visualize insights for research, using NLP, Machine Learning, and Deep Learning techniques. You will work closely with stakeholders to optimize data mining and improve the accuracy of insights generated. What You ll Do: Execute High-Impact Data Science Projects: Translate research objectives into actionable data and facts using social media and Gartner's internal/external data. Ad-hoc Modeling and Analytical Insights: Provide modeling and analytical insights to inform strategic and operational initiatives. Analyze Unstructured Data: Use advanced data science techniques to analyze unstructured text data, identifying insights and patterns. Interpret and Apply Findings: Align findings with business objectives and translate them into actionable business insights. Solve Business Challenges: Leverage Data Science, ML, and NLP to address pressing business challenges. Stakeholder Interaction: Collaborate with internal and external stakeholders to refine and improve findings. Data Science Driven Initiatives: Drive initiatives with some guidance while building strong domain expertise. Multi-tasking & Agility: Handle different projects in a fast-paced environment with strict SLAs and tight turnaround times. What You ll Need: Education: A fresher with a Master's in Engineering, Computer Science, Computer Applications, Statistics, Mathematics, Applied Mathematics, or Data Science. Alternatively, a B.E./B.Tech + Masters in Advanced Analytics or Data Science. Experience: 1-3 years of hands-on AI/ML experience, especially in Text Mining, NLP, and text analytics. Technical Skills: Expertise in Python (Pandas, Numpy, scikit-learn), SQL, TensorFlow, and other data science tools. Familiarity with AWS/Azure environments for training, testing, or deploying models. Machine Learning & NLP Knowledge: Ability to train, fine-tune, or apply ML, Deep Learning, LLMs, and NLP models. In-depth knowledge of NLP concepts and application experience. Data Preparation Skills: Expertise in data cleaning, normalization, and preparation for model training or inference. Analytical Mindset: Strong ability to identify patterns in unstructured datasets and provide actionable insights. Communication Skills: Strong written and verbal communication with the ability to structure clear, concise, and meaningful communication. Critical Thinking & Problem-Solving: Strong analytical skills and the ability to think independently to solve complex problems. Eagerness to Learn: A passion for learning about new technologies in the IT industry, Data Science, and Machine Learning. Research Techniques Understanding: Robust understanding of primary and secondary research methods. What We Offer: Flexible Hybrid Work Environment: Flexibility to work virtually when productive and meet colleagues in person for engaging, purposeful collaboration. Professional Growth: Gartner offers world-class benefits, competitive compensation, and tremendous rewards for top performers. Inclusive Work Culture: Diverse teams from various backgrounds and an environment that values collaboration and team success. Recognition as a Top Workplace: Gartner is consistently recognized as a great place to work worldwide. Join Gartner and contribute to world-class insights while developing cutting-edge technologies in the data science domain. We offer opportunities to grow, thrive, and make an impact! Qualification : A fresher with a Master's in Engineering, Computer Science, Computer Applications, Statistics, Mathematics, Applied Mathematics, or Data Science. Alternatively, a B.E./B.Tech + Masters in Advanced Analytics or Data Science.

Product Analyst - Team Lead (Risk) Location: Gurugram, Haryana (On-site) Company: Paytm India s Leading Mobile Payments & Financial Services Platform About Paytm Paytm is India s pioneer in mobile payments and financial services distribution, transforming commerce for millions of small businesses. Our mission is to empower half a billion Indians by bringing them into the mainstream economy using innovative technology. About the Team The Credit Risk Product Team plays a critical role in lending by developing efficient, scalable, and compliant risk assessment models. The team partners with data scientists, engineers, and business stakeholders to refine underwriting processes through advanced analytics and machine learning optimizing loan performance and minimizing defaults. Role Overview We are looking for a detail-oriented Product Analyst to lead credit risk initiatives. In this role, you will implement and optimize credit risk policies while ensuring compliance with regulatory requirements. You will work closely with data scientists, product managers, and credit teams to enhance underwriting models and risk decision frameworks. Key Responsibilities Analyze credit risk across multiple credit products, such as credit cards, merchant loans, and personal loans. Collaborate with business teams to understand and implement credit risk policies on the platform. Monitor and evaluate the performance of risk policies; provide actionable feedback to Product and Policy teams. Leverage alternative data sources, machine learning models, and traditional credit assessments to improve risk evaluation. Conduct testing, scenario analysis, and policy resilience measurement. Track key risk indicators (KRIs) and generate insights for management. Ensure compliance with regulatory guidelines and internal risk frameworks. Work with product and technology teams to embed risk-based decision-making into lending workflows. Qualifications 1 2 years of relevant experience, preferably in fintech or banking. Strong proficiency in SQL and Python for data analysis and manipulation. Basic understanding of APIs and streaming platforms like Kafka is a plus. Excellent analytical, problem-solving, and communication skills. Ability to thrive in a fast-paced, dynamic environment and collaborate cross-functionally. Educational background: B.Tech from reputed institutes like NIT, BITS, or equivalent. Be part of India s largest fintech lending ecosystem with 500+ million users and 21+ million merchants. Work in a fun, energetic environment designed to help you reach your full career potential. Unique opportunity to shape India s largest digital lending story and drive financial inclusion.

Prompt Engineer (Software Engineer) Analyst Location: Gurgaon, India (On-site) Function: Content Engineering Experience: 0-1 years About GlobalLogic GlobalLogic, a Hitachi Group Company, is a leading digital engineering partner to some of the world s largest and most innovative companies. Since 2000, we have driven the digital revolution, creating cutting-edge digital products and experiences that transform businesses and industries globally. At GlobalLogic, we prioritize a culture of caring, continuous learning, and balance, fostering an environment where creativity and innovation thrive. Role Overview As a Prompt Engineer, you will focus on designing, developing, and optimizing prompts for natural language understanding systems, especially conversational AI and chatbots. This role requires a strong foundation in Python, data science, and natural language processing, combined with hands-on experience in prompt engineering, deep learning models, and relevant AI frameworks. Key Responsibilities Design and develop effective prompts for conversational AI and NLU systems. Collaborate with engineers and data scientists to integrate and refine prompts. Analyze user behavior and model outputs to enhance prompt quality and response accuracy. Optimize algorithms to improve prompt generation efficiency and effectiveness. Continuously update knowledge on NLP advancements and apply innovative techniques. Test and evaluate prompts for quality, relevance, and user experience improvement. Work cross-functionally to ensure seamless integration of prompts into products. Identify and resolve prompt-related challenges to boost conversational AI performance. Qualifications Bachelor s degree in Artificial Intelligence, Machine Learning, or related field (B.Tech freshers welcome). Strong programming skills in Python and experience with databases and data science methodologies. Proven knowledge of NLP, prompt engineering, and conversational AI or chatbot systems. Familiarity with deep learning concepts including transformers, GANs, VAEs, and large language models (LLMs). Proficiency with AI frameworks such as TensorFlow, PyTorch, and spaCy. Ready to work on-site with rotational shifts (5 working days, 2 weekly offs). Immediate joining preferred. Inclusive, caring culture fostering acceptance and collaboration. Robust learning and development opportunities to accelerate your career growth. Meaningful work on innovative projects shaping the future of AI and digital experiences. Work-life balance with flexible arrangements and supportive policies. A high-trust, ethical organization valuing integrity and transparency. Qualification : Bachelors degree in Artificial Intelligence, Machine Learning, or related field

Job Title: Computer Vision Researcher (3D) AI & Deep Learning | Spyne (Gurgaon) Location: Gurgaon, India | Work Mode: Full-Time, Onsite | Experience: 1 3 Years Keywords: Computer Vision Jobs India, Deep Learning Researcher, GAN Engineer, AI Research Jobs, ML Engineer, Generative AI Careers About Spyne Spyne is transforming the future of automotive retail with next-gen Generative AI. From AI-powered car visuals to a full-stack ecosystem for online vehicle commerce, we re enabling dealerships to create, price, and market inventory faster and smarter. Backed by $16M Series A funding from top VCs like Vertex Ventures and Accel Rapid expansion across the US and EU markets Achieved 5x revenue growth in 15 months aiming for another 3-4x in 2025 Leading the GenAI wave with AI-driven sourcing, pricing, CRM, and Agentic AI tools Role Overview: Computer Vision Engineer / Researcher We re hiring a passionate Computer Vision Engineer (3D) to join our Research & AI Product team. You ll work on state-of-the-art deep learning models especially GANs to develop and deploy scalable image processing and enhancement pipelines across automotive, e-commerce, food, and real estate domains. You ll play a pivotal role in building innovative AI-powered products that impact millions of images and videos, optimizing workflows for global businesses. Key Responsibilities Research & Experimentation Stay up to date with cutting-edge publications in AI, Computer Vision, and Deep Learning. Prototype innovative approaches from top-tier conferences (CVPR, NeurIPS, ICCV). AI Model Development & Deployment Train, fine-tune, and deploy models for image enhancement, segmentation, and classification using PyTorch/TensorFlow. Work on GAN Architectures Develop and optimize Generative Adversarial Networks (GANs) for image inpainting, background removal, super-resolution, and 3D scene generation. Scalable AI Infrastructure Collaborate with MLOps and Data Engineering teams to build robust AI pipelines on cloud platforms (AWS, GCP, Azure). Cross-Team Collaboration Work closely with Product Managers, Software Engineers, and Data Scientists to align AI capabilities with business goals. Mentorship & Guidance Contribute to a culture of innovation by mentoring junior researchers and participating in peer reviews. Requirements & Qualifications Education & Experience B.Tech / M.Tech in Computer Science, Artificial Intelligence, or related field (Tier 1 or Tier 2 institute preferred) 1 3 years of hands-on experience in Computer Vision, AI model development, and Deep Learning Technical Skills Deep Learning Frameworks: Strong expertise in PyTorch or TensorFlow Generative Models: Proven experience with GANs for real-world use cases Programming: Proficiency in Python, plus experience in C++ or C# Image Processing Libraries: OpenCV, PIL, NumPy, Scikit-image Cloud Platforms: Hands-on experience deploying models on AWS, GCP, or Azure Research Mindset: Ability to implement novel ideas from AI research papers into practical solutions Soft Skills & Work Ethic Strong analytical and problem-solving capabilities Excellent communication and collaboration skills Comfort in a high-performance, office-first environment (5 days/week) Familiarity with Agile, Git, Jira, and collaborative development tools At Spyne, we empower careers not just fill positions. People-First Culture: Supportive team, open communication, and trust Career Acceleration: Fast growth with performance-based promotions and ownership opportunities Health & Insurance Benefits: Comprehensive GMC, GPA, GTLI coverage for employees and families Continuous Learning: Access to LinkedIn Learning, in-house mentorship, and AI research projects Work from Office Advantage: Real-time innovation, mentorship, and collaboration at our Gurugram HQ Competitive Salary + Equity: High-impact role with potential for stock options If you're excited to work on groundbreaking AI + 3D computer vision products, thrive in a startup environment, and want to shape the future of AI-powered automotive retail, we want to hear from you. Apply now and be part of Spyne s journey as we redefine how the world sees and sells cars! Qualification : B.Tech / M.Tech in Computer Science, Artificial Intelligence, or related field (Tier 1 or Tier 2 institute preferred)

Job Title: Product Manager (LLMs & AI) Location: Gurgaon, Haryana Experience: 3-7 years Department: Product Management Employment Type: Full-Time About Spyne At Spyne, we are redefining how cars are marketed and sold with cutting-edge Generative AI. What started as a bold idea using AI-powered visuals to help dealers sell online faster has grown into a full-fledged AI-first automotive retail ecosystem. Backed by $16M in Series A funding from Vertex Ventures, Accel, and other top investors, we are scaling rapidly: Expanded across US & EU markets. Launched industry-first AI-powered Image & 360 solutions. Achieved 5X revenue growth in 15 months, with a goal for 3-4X growth this year. We are now rolling out an end-to-end GenAI Automotive Retail Suite and expanding into the US market to bring our AI-driven products to 3,000-4,000 dealers. What We Are Looking For We are looking for an experienced Product Manager to lead the development of Large Language Model (LLM)-powered applications and AI agents. This role will focus on harnessing the power of LLMs (e.g., OpenAI s GPT, Claude, or similar models) to create advanced, context-aware conversational agents and automation systems. As a Product Manager (LLMs & AI), you will work on defining and delivering AI solutions that transform the user experience, streamline processes, and unlock new business opportunities for Automotive dealers and buyers. This is a critical role in shaping Spyne s product strategy, translating user needs into AI-driven solutions, and collaborating with cross-functional teams to deliver innovative, AI-powered products. Product Strategy & Vision: Define and execute the roadmap for LLM-powered applications and AI agents, aligning with market trends and user needs. AI Innovation: Explore cutting-edge applications like chatbots, decision-support systems, and automation tools. Research & Experimentation: Collaborate with engineers and data scientists to fine-tune and deploy LLMs for real-world use cases. AI Advancements: Stay updated on emerging capabilities like multi-turn dialogue, in-context learning, and fine-tuning techniques. AI Agent Development: Build context-aware AI agents that integrate seamlessly into user workflows. Automation Solutions: Develop AI-driven tools for automating tasks like email responses, scheduling, and data extraction. User Experience & Adoption: Convert user pain points into intuitive AI-driven solutions with explainable outputs. Seamless AI-Human Interaction: Ensure smooth AI adoption by refining user interfaces and interactions. Cross-Functional Collaboration: Work closely with Engineering, Data Science, and Design teams to prototype and scale LLM-based features. AI Market Positioning: Collaborate with Sales and Customer Success teams to position AI capabilities as a key differentiator. Performance Metrics: Define and track KPIs such as accuracy, response time, and user engagement. Continuous Optimization: Enhance AI model efficiency and user satisfaction through iterative improvements. What You Must Have 1 3 years of product management experience in AI, SaaS, or data-driven products. Proven experience building or scaling LLM-powered applications (e.g., GPT, Claude). Strong familiarity with fine-tuning, prompt engineering, context management, and model evaluation. Ability to communicate AI concepts to non-technical stakeholders. Hands-on experience with Figma, Jira, and LLM APIs (OpenAI, Anthropic, Hugging Face). Data-driven mindset with a strong grasp of AI product metrics. Thrive in fast-paced, ambiguous environments. Strong Culture: A supportive and collaborative work environment that encourages innovation. Transparency & Trust: High levels of autonomy and trust in decision-making. Competitive Salary & Equity: Stock options for top performers. Health Insurance: Comprehensive coverage for employees and their dependents, including GMC, GPA, and GTLI coverage. Dynamic Growth Environment: Join a fast-paced, high-growth setting that will accelerate your professional development. Shape the Future of AI-Powered Automotive Retail If you're passionate about AI and want to play a key role in transforming the automotive retail experience, join Spyne and help us define the future of AI-powered automotive retail!

Job Title: Senior Data Engineer Location: Gurugram, Haryana, India Company: Builder.ai About Builder.ai At Builder.ai, we re transforming software development so that anyone regardless of technical expertise or budget can bring their software ideas to life. From startups to global enterprises like BBC, Makro, and Pepsi, we ve empowered thousands of customers around the world. With over $450M in Series D funding, including backing from Microsoft and QIA, and recognition from Fast Company as one of 2023 s Most Innovative Companies in AI, we are scaling rapidly and redefining what s possible in software and AI. Life at Builder.ai We believe in experimentation, ownership, and constant improvement. Our team of 800+ is spread across the globe but united by our shared HEARTT values: Heart, Entrepreneurship, Accountability, Respect, Trust, and Transparency. We reward your skills with: Stock options in a hyper-growth company International offsites Unlimited learning opportunities A culture that values diversity, innovation, and impact About the Role As a Senior Data Engineer, you'll be a foundational part of our growing Data & Analytics team. We're not just building pipelines we're engineering the data backbone for an entire platform that powers AI-driven software creation, operational intelligence, and customer solutions. This role will focus on building robust, scalable, and efficient data systems, and working with Data Scientists, Analysts, and Software Engineers to ensure our data infrastructure is best-in-class. What You ll Be Doing Own and operate end-to-end data pipelines across critical business domains Optimize compute, storage, and query performance using modern big data technologies Manage and evolve our CI/CD workflows and data infrastructure Improve data accuracy, integrity, and reliability for mission-critical datasets Collaborate with cross-functional teams (Analytics, AI, Product) to deliver business value Drive best practices in data engineering, architecture, and tooling Lead projects independently while clearly communicating with stakeholders on timelines and expectations Mentor junior data engineers and contribute to a strong data culture Must-Have Experience: Expert in ETL orchestration tools (e.g., Dagster, Airflow, Luigi) Proficient in SQL databases (e.g., Snowflake, PostgreSQL) Deep understanding of big data systems (e.g., Spark, Hadoop, Hive) Strong programming in Python Experience with DBT and data modeling best practices Deep experience with cloud platforms (especially Azure) Familiarity with streaming data systems (e.g., Kafka, Kinesis) Exposure to MLOps and experience delivering clean, usable datasets to AI/ML teams Experience with CI/CD and Agile environments Nice to Have: Background in ML infrastructure or knowledge graphs Experience working in product-led B2B/SaaS organizations Contributions to open-source data tools What You ll Get Quarterly discretionary performance pay Stock options in a $450M-funded scale-up 24 days annual leave + public holidays 2 Builder Family Days + Christmas/New Year break Fully covered private medical insurance Free lunch at our Gurugram HQ Referral bonus scheme Trips abroad and global collaboration Why You Should Join If you re ready to build world-class data systems that power AI at scale, and want to help shape how software will be built in the future this is your moment. Apply today and transform the way software is created one data pipeline at a time.

We are seeking a skilled and driven Senior Data DevOps Engineer with strong MLOps expertise to join our team. The ideal candidate will have a deep understanding of data engineering, automation in data pipelines, and operationalizing machine learning models. The role requires a collaborative professional capable of designing, deploying, and managing scalable data and ML pipelines that align with business goals. Responsibilities Develop, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment Implement and maintain infrastructure for data processing and model training using cloud-based tools and services Automate data validation, transformation, and workflow orchestration processes Collaborate with data scientists, software engineers, and product teams to ensure seamless integration of ML models into production Optimize model serving and monitoring to enhance performance and reliability Maintain data versioning, lineage tracking, and reproducibility of ML experiments Proactively identify opportunities to improve deployment processes, scalability, and infrastructure resilience Ensure robust security measures are in place to protect data integrity and compliance with regulations Troubleshoot and resolve issues across the data and ML pipeline lifecycle Requirements Bachelor s or Master s degree in Computer Science, Data Engineering, or a related field 4+ years of experience in Data DevOps, MLOps, or related roles Strong proficiency in cloud platforms such as Azure, AWS, or GCP Experience with Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible Expertise in containerization and orchestration technologies (e.g., Docker, Kubernetes) Hands-on experience with data processing frameworks (e.g., Apache Spark, Databricks) Proficiency in programming languages such as Python, with knowledge of data manipulation and ML libraries (e.g., Pandas, TensorFlow, PyTorch) Familiarity with CI/CD tools (e.g., Jenkins, GitLab CI/CD, GitHub Actions) Experience with version control tools (e.g., Git) and MLOps platforms (e.g., MLflow, Kubeflow) Strong understanding of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana) Excellent problem-solving skills and the ability to work independently and as part of a team Strong communication and documentation skills Nice to have Experience with DataOps concepts and tools (e.g., Airflow, dbt) Knowledge of data governance and tools like Collibra Familiarity with Big Data technologies (e.g., Hadoop, Hive) Certifications in cloud platforms or data engineering We offer Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications Opportunity to share your ideas on international platforms Sponsored Tech Talks & Hackathons Unlimited access to LinkedIn learning solutions Possibility to relocate to any EPAM office for short and long-term projects Focused individual development Benefit package: Health benefits Retirement benefits Paid time off Flexible benefits Forums to explore beyond work passion (CSR, photography, painting, sports, etc.) Qualification : Bachelors or Masters degree in Computer Science, Data Engineering, or a related field

We are seeking a highly experienced Senior Snowflake Data Engineer to join our team. The ideal candidate will be responsible for designing and implementing robust data solutions within Snowflake, ensuring they are efficient, secure, and scalable. Responsibilities Engage in Snowflake data modeling to create and maintain optimized models tailored for data ingestion and analytical needs Develop and sustain ETL pipelines to consolidate data from diverse sources into Snowflake while preserving data integrity Fine-tune the performance of Snowflake deployments, optimize storage usage, and manage data partitioning for prompt and reliable data access Establish strong data security measures, implement role-based access controls, and apply data masking techniques to uphold data governance standards Leverage tools like dbt and Apache Airflow for scheduling and automating data processes and pipeline surveillance Cooperate closely with cross-functional teams including data scientists and business analysts to solve intricate data issues and carry out effective troubleshooting Create detailed documentation and reports on data architectures, ETL processes, and system operations to facilitate clear communication and knowledge sharing across the organization Requirements 5-8 years of experience in a data engineering role Background in information warehousing with AWS or Azure, utilizing DBT, Snowflake Proficiency in Python programming, workflow management tools including Argo, Oozie, or Airflow Snowflake modeling fundamentals like roles, schema, and databases Competency in data vault modeling, designing, and developing data transformation pipelines using DBT We offer Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications Opportunity to share your ideas on international platforms Sponsored Tech Talks & Hackathons Unlimited access to LinkedIn learning solutions Possibility to relocate to any EPAM office for short and long-term projects Focused individual development Benefit package: Health benefits Retirement benefits Paid time off Flexible benefits Forums to explore beyond work passion (CSR, photography, painting, sports, etc.) Qualification : 5-8 years of experience in a data engineering role