Top Data Science Jobs in India

Lead data science strategies and insights for assigned clients. Manage multiple analytics engagements and a team, integrate and prepare datasets, apply data science methods to generate recommendations, communicate findings, and set team development objectives while staying current on industry trends.

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

Lead AI/ML initiatives as an individual contributor: design and implement ML solutions, develop and maintain code, define architecture, guide data infrastructure, and collaborate with cross-functional teams to solve business problems.

The Facilitator will deliver academic support in Data Analytics through live sessions, tutoring, and quality assurance, while collaborating on curriculum enhancements and mentoring others.

Lead data science for supply chain demand planning: clean and analyze large datasets, build and maintain predictive models, drive 30-month demand planning, monitor MAPE/BIAS, coordinate cross-functional stakeholders, deploy improvements (Six Sigma), train demand planning teams on tools (o9), and report forecast KPIs.

Lead and grow the Shipping Analytics team to define metrics, drive experimentation, build AI-enabled analytics (including LLMs), deliver insights that influence product and business decisions, and scale analytics infrastructure and self-serve tooling.

Lead design and production of high-performance data and search architectures (ELK, PostgreSQL), build RAG and multi-agent AI systems, deploy hybrid multi-cloud solutions (AWS/Azure/GCP), containerize and automate MLOps pipelines, mentor engineers, and own end-to-end feature delivery and architecture.

Lead data science initiatives using advanced statistical techniques and machine learning to produce actionable insights. Partner with cross-functional teams to design data-driven solutions, manage and ensure integrity of large datasets, develop predictive models to forecast trends, and communicate results to stakeholders while staying current on emerging technologies.

Support Applied AI team by writing production-quality Python and optimized Snowflake/SQL queries to prepare and validate large datasets, run EDA, build evaluation datasets and benchmarking, and assist product managers and data scientists with experimentation, root-cause analysis, and ML/AI pipeline evaluation. Document and communicate findings to stakeholders.

Support AI workflows by building and optimizing Snowflake SQL, writing production-quality Python for data transformation and pipelines, curating evaluation datasets and metrics, performing exploratory data analysis to find quality issues, and partnering with product managers and data scientists to support experimentation, model evaluation, and automation.

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

Design and implement test plans, write test code, validate software/SDKs and AI models for geospatial AI products. Troubleshoot issues, collaborate with data scientists, create documentation, samples, tutorials, and develop pretrained geospatial AI models for imagery, 3D, and text.

Create and curate AI/ML and data science course content, deliver instructor-led and virtual training, mentor candidates on project work, and stay current with emerging AI technologies. May require travel.

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

Lead and manage the Data Science team delivering MMM, incrementality, RBA, and forecasting models. Oversee end-to-end model development, validation, productization, API design for agent consumption, mentor staff on Bayesian and causal methods, and coordinate with Data Architecture and Media Effectiveness teams.

Lead and deliver measurement and marketing-science models (MMM, incrementality, RBA, forecasting); manage model pipelines, validate methodology, productize agentic models, mentor data scientists, coordinate with data architecture, and support GTM for analytics products.

Lead and manage a team of Data Scientists and Data Analysts, establishing data standards and practices in Stripe's India office while driving data-centric decision-making across the organization.

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.

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 a team of data scientists to apply data mining techniques, conduct statistical analysis, and build predictive systems for technology intelligence.

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.