Top Data Science Jobs in India

The Manager of Product Management will develop product vision and strategy, collaborate with cross-functional teams on AI/ML platform products, and maintain agile processes to enhance business and customer outcomes.

Lead product definition and lifecycle for Knowledge Center capabilities: write use cases and functional requirements, prioritize roadmaps and budgets, collaborate with engineering, QA, technical writers and stakeholders, and work in Agile sprints to deliver SaaS/platform features that improve customer experience.

The Manager of Product Management for AI/ML Model Governance is responsible for defining product vision, collaborating with teams, managing backlogs, and ensuring customer-centric product development.

Lead India product strategy for Adyen's payments suite, own go-to-market fit, navigate regulations, build and manage a product team, align engineering, data, and commercial teams to scale localized payment solutions.

Lead end-to-end product development for AI-powered pricing and optimization solutions in manufacturing and distribution. Define roadmap, partner with data science and engineering to translate ML outputs into customer experiences, set metrics, and align stakeholders across sales, UX, and analytics.

Design and implement technical features, collaborate with clients, write production-ready code, ensure quality deliverables, mentor team members, and implement ML models on large scale.

Drive regional technical vision and strategy for CrowdStrike in India: influence product roadmap, engage customers, partners, governments and media, identify new technologies and partnerships, and provide cross-functional strategic guidance to Product, Sales, CTOs and engineering teams.

The Senior Engineer, CAD will innovate memory and storage solutions, focusing on AI systems, data science, and advanced technologies in semiconductor domains.

Lead and manage a team of Machine Learning Engineers and Data Scientists to develop ML solutions that enhance user engagement and support business objectives in digital entertainment.

Lead Lean Six Sigma process-improvement and digital-transformation initiatives across business and technology teams. Design target operating models, identify automation and AI/ML/NLP opportunities, partner with product owners to deliver MVPs, and drive change management and stakeholder engagement to improve client experience and operational efficiency.

The role leads a team to provide healthcare-focused insights through analytics and data science, requiring strong people management, technical oversight, and a healthcare domain understanding.

The AI/ML Engineer/Architect will lead prototyping and productization of AI/ML technologies, develop governance frameworks, and collaborate across functions to align with strategic goals.

Technical product manager supporting AI and agentic capabilities for Payment Performance Intelligence. Execute AI product strategy and roadmap, translate customer needs into technical requirements, coordinate with engineering and data science, support backlog refinement and releases, validate use cases through research and experimentation, and contribute to go-to-market and enablement activities.

Develop, deploy, and scale Generative AI solutions (RAG, agents, LangGraph) for telecom managed services. Integrate GenAI with BSS/OSS and telecom APIs, build automation and QA capabilities, and collaborate across global teams to deliver production-ready AI/ML systems.

Lead market-wide product strategy and analysis across APAC: identify opportunities, quantify value, develop proposals, manage program pipelines, and deliver data-driven recommendations with cross-functional stakeholders.

Support Global Supply marketing and administrative functions: execute digital campaigns, assist event planning and customer service, maintain regulatory documentation, provide analytics and KPI insights, participate in process improvements, and support marketing/medical teams using digital and AI tools.

Design, implement, and deploy ML and Bayesian models for commercial forecasting, segmentation, classification, and promotional effectiveness. Build ML pipelines, create dashboards, and partner with commercial and insights teams to translate analytics into actionable recommendations for pharma stakeholders.

Lead or contribute to moderately complex data science initiatives, analyzing large structured and unstructured datasets, building statistical and machine learning models, executing experiments, and delivering actionable insights. Collaborate with stakeholders, mentor junior staff, and communicate recommendations to non-technical audiences to influence business strategy and resolve analytic problems.

Lead and grow a data science team to deliver analytical and predictive models, engage stakeholders, identify data-driven opportunities, allocate resources, mentor staff, and communicate actionable insights to non-technical audiences.

Lead moderately complex data science initiatives: analyze large structured and unstructured datasets, build advanced statistical and ML models, run experiments, generate actionable insights and recommendations, communicate findings to non-technical stakeholders, and mentor junior staff.

Lead complex data science initiatives across Consumer Lending, designing advanced statistical models and experiments, interpreting large datasets, advising stakeholders, mentoring staff, ensuring model governance and regulatory compliance, and delivering actionable insights and visualizations to influence senior leadership decisions.

Develop statistically effective algorithms and apply machine learning, deep learning, and generative AI techniques to high-dimensional problems. Use hypothesis testing, data mining, and big-data tools to identify trends, build predictive models and recommender systems, collaborate with clients and stakeholders, and evaluate emerging datasets and technologies for scalable analytical solutions.

Lead a team of Data Scientists and ML Engineers to develop AI-driven healthcare applications. Provide technical guidance, mentorship, and ensure high-quality delivery of scalable solutions.

The role involves developing analytics and insights for Procurement, applying data analytics, establishing data governance, and collaborating with stakeholders to enhance decision-making and operational effectiveness.

The Engineering Manager will lead AI & ML initiatives focused on data collection, overseeing technical projects and developing a high-performing team. Responsibilities include providing technical direction, mentoring staff, ensuring system reliability, and maintaining data integrity and security. The role requires expertise in NLP and data processing with an emphasis on collaborative leadership and continuous innovation.