Top Data Science Jobs in India

Support provider-focused analytics by developing descriptive, predictive, and generative AI-enabled analytics. Collaborate with product owners, data engineering, governance, and clinical teams to build data products, ensure data quality, enable RAG workflows, and communicate business value to stakeholders.

Lead advanced marketing analytics and measurement initiatives, build attribution, MMM and predictive models using structured and unstructured data, manage vendor relationships, present insights to senior stakeholders, and drive media test-and-learn and measurement roadmap execution across acquisition, engagement, and retention.

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.

Lead design, development, and deployment of enterprise-scale AI/ML solutions, specializing in LLMs and NLP. Build and optimize models, design scalable MLOps pipelines, drive AI strategy, evaluate new technologies, ensure production reliability and responsible AI practices, and mentor data science teams while collaborating with cross-functional stakeholders.

Lead design, development, and deployment of enterprise AI/ML solutions. Build and fine-tune LLMs, develop NLP pipelines, design scalable MLOps systems, mentor teams, and drive model lifecycle, evaluation, and responsible AI practices.

Lead end-to-end data science projects: explore data, develop/validate models, automate pipelines, integrate models into business workflows, and advise stakeholders on leveraging data science and Generative AI for high-impact solutions.

The Data Science Manager leads teams in developing machine learning models and data strategies, ensuring data governance, mentoring staff, and driving actionable insights through cross-functional collaboration.

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.

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.

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.

Deliver live instruction, on-demand tutoring, video explanations, and QA reviews for Data Analytics learners. Mentor new experts, maintain QA standards (≥80%), contribute curriculum updates, and support learner engagement and academic quality improvements.

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 Principal Data Science Engineer will develop advanced AI solutions for travel, integrating ML models and improving automation in travel systems while mentoring junior staff.

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.

Design, develop, and deploy predictive models and scalable analytics solutions. Perform EDA, feature engineering, model evaluation, and data visualization. Build interactive dashboards, ensure data quality and governance, collaborate with stakeholders and engineering teams, and present actionable insights to drive business decisions.

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

The Senior Advisor - Data Science leads complex data science projects, applying advanced statistical and ML techniques to solve business problems. Responsibilities include model development, validation, and mentoring junior data scientists, while ensuring scalability and reliability in production environments.

Lead and scale data science teams delivering production-grade forecasting, optimization, and simulation across supply chain products. Own delivery outcomes, enforce engineering and governance standards, mentor and grow talent, align solutions with architecture and CI/CD, and influence senior stakeholders to translate analytics into business decisions while driving adoption of AI and delivery tooling.

Lead design and maintenance of data pipelines and data lake, define data models and catalogue (PolyBase), develop analytics and ML models, drive data-driven decision-making, collaborate with stakeholders and promote advanced analytics across the organization.

Lead insights and analysis for assigned clients by applying data science methods, managing multiple analytics engagements, preparing and integrating datasets, communicating findings, and developing the analytics team through training and escalation management.

Lead insights and analysis for assigned clients by applying data science methods, managing multiple analytics engagements, preparing and integrating datasets, communicating findings, and developing the team through training and objectives.

Lead analytics and ML initiatives for Focus Category, building and deploying predictive models and AI-powered analytics platforms (NL-to-SQL, LLM features). Partner with product and business stakeholders to design experiments, craft dashboards, integrate data sources, and productionize ML/LLM pipelines and visualizations to drive product discovery, measurement, and growth.

Lead clinical data management activities for one or more trials, ensuring data integrity, regulatory compliance, inspection readiness, and delivery of CRFs, datasets, and review plans. Coordinate cross-functional stakeholders, manage vendors, define eCRF requirements, provide team leadership, training, and continuous improvement.