Top Data Science Jobs in India

Lead the Data Science team for Lending at Grab, overseeing credit risk modeling, guiding ML strategies, and partnering with stakeholders for data-driven insights and model governance.

The Director of Data Science will lead the development of AI systems, manage a team, and drive knowledge sharing while ensuring project alignment with business goals.

The Director of AI/ML & Data Science will lead data science teams, establish technical rigor, manage cross-functional collaborations, and drive initiatives in AI, NLP, and analytics.

The Director will lead data science efforts to derive insights from large datasets, enhance data products, and improve data science methodologies, while collaborating with various teams at Gartner.

The Data Science & Machine Learning Lead will drive ML initiatives, translating business problems into scalable solutions, leading model development, and ensuring measurable business impact.

Lead data science initiatives by defining roadmaps, managing teams, and engaging clients, while driving innovative AI and analytics solutions.

The Associate Director of Data Science will lead analytics model development, drive business growth, and mentor data analysts within a cloud services framework.

Drive strategic initiatives in healthcare analytics, manage consulting projects, deliver data-driven recommendations, and engage stakeholders across the Life Sciences industry.

The role involves managing AI-driven business transformations in Life Sciences, enhancing performance through data and analytics, and leading client relationships to foster innovation.

Manage consulting projects in healthcare analytics, providing strategic advisory services, and developing data-driven recommendations to enhance business performance.

Develop and deploy NLP and GenAI applications/products, conduct ML experiments, and create APIs and UI for user interaction.

As a Data Science Associate, you will apply data-driven methodologies to solve complex modeling challenges, utilizing various statistical techniques and programming languages to analyze large datasets and support decision-making.

The Principal-Global Feasibility Data Science role involves managing complex feasibility assessments independently and collaborating with various stakeholders to derive innovative solutions.

The role involves leading data science initiatives, optimizing processes, developing AI frameworks, and ensuring ethical compliance while engaging with users.

Lead a team of data scientists to leverage analytics and machine learning in the life sciences sector, optimizing outcomes through data-driven insights.

The Post Doctoral Scientist will analyze large-scale datasets related to cardiometabolic diseases, using statistical and computational techniques to identify genetic factors and support therapeutic development.

As a Product Engineer, you will ensure quality and usability of geospatial AI tools, design test plans, validate software, and document technical processes.

Manage and mentor a team of data analysts, design and deploy advanced analytics models, and engage with clients to translate business challenges into analytics solutions.

Lead data science initiatives, develop and evaluate models, translate business problems into actionable insights, and mentor junior analysts. Collaborate with teams to operationalize AI-driven insights for measurable business impact.

As a Data Science Consultant, you will implement ML algorithms, support clients with the Luminate Planning suite, and mentor junior members while maintaining data integrity and conducting analyses.

The Senior Data Science Engineer will apply statistical and machine learning techniques to analyze airline data, optimizing revenue and enhancing customer experience, while collaborating with experts and developers.

As a Data Scientist, you will enhance data productivity, develop models, collaborate with business stakeholders, and provide insights to improve product usability and reseller performance.

The AI Capability Lead will define the AI strategy, architect enterprise AI solutions, and mentor teams while advising clients on AI implementation.

Lead design, development, and deployment of multi-agent, agentic AI solutions using LangGraph, LLM orchestration, RAG, and RL-based fine-tuning. Build scalable architectures, integrate vector databases and knowledge graphs, run PoCs to demonstrate business impact, and mentor AI engineers and data scientists for production-grade autonomous agents.

Lead research, design, and deployment of multi-agent, agentic AI systems using LangGraph and LLM orchestration. Build memory-augmented agents, implement RAG with vector DBs, apply RLHF/RLAIF, prototype PoCs, scale production architectures, and mentor AI engineers.