Top Data Science Jobs in India

Lead end-to-end UX strategy and execution for complex healthcare analytics products. Drive cross-functional collaboration, market analysis, AI-driven prototyping, accessibility and privacy compliance, scale UX standards, mentor designers, and support go-to-market product positioning and roadmaps.

Own a Business Onboarding Verification workstream end-to-end: define problems, set roadmap, translate ambiguous KYB issues into measurable product requirements, partner cross-functionally, launch with guardrails, and iterate to reduce manual review, operational cost, and customer friction while improving controls and auditability.

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.

Lead product strategy and roadmaps for data science, ML, and cloud products in healthcare. Translate business needs into technical requirements and user stories, drive Agile delivery, analyze user and market data to set metrics, design and deploy AI-powered solutions responsibly, mentor junior PMs, and ensure compliance with healthcare regulations throughout the product lifecycle.

Support end-to-end product lifecycle for healthcare-focused data science, cloud, and analytics products. Define product strategy and roadmap, act as Product Owner to prioritize backlog, translate business needs into technical requirements and user stories, collaborate with engineering and data science to deliver AI-enabled solutions, and support product launches, adoption, and performance measurement.

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.

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.

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.

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.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime use cases. Apply supervised and unsupervised methods, execute model lifecycle (feature engineering, training, validation, monitoring), support model governance, partner with MLOps for CI/CD, deliver explainable outputs, and leverage GenAI/LLMs for unstructured data extraction and summarization.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime. Perform end-to-end model lifecycle work (feature engineering, training, validation, calibration, monitoring), support model governance and audits, collaborate with SMEs and MLOps for CI/CD and productionization, deliver interpretable explainability outputs, and incorporate GenAI/LLMs for unstructured text signal extraction.

Lead design, prototyping, and production deployment of LLM- and GenAI-based solutions for compliance and risk. Build agentic AI, RAG/GraphRAG, MCP integrations, knowledge graphs, Python services, and partner across Compliance, Technology, and Product to operationalize AI with governance and best practices.

Design and implement enterprise AI solutions using LLMs, Generative and Agentic AI. Build RAG/GraphRAG, knowledge graphs, MCP integrations, orchestration workflows, scalable Python services, APIs, and dashboards. Collaborate with compliance, tech, and business stakeholders and contribute to engineering standards and AI governance.

Support development of credit risk and business intelligence analytic solutions: build predictive models, extract and analyze large datasets, produce insights and presentations, partner with cross-functional teams, and support client engagements using statistical and big-data tools.

Lead development and delivery of analytic solutions across credit, fraud, insurance, and marketing. Manage small teams and client engagements, design and deploy ML/DL models, implement model governance and monitoring, and translate technical work into business recommendations. Contribute to research, mentor junior staff, and support proposals through production deployments using R, Python, and big-data/cloud tooling.

Lead a team of machine learning engineers and data scientists to develop and deploy AI solutions in healthcare, optimizing workflows and model performance.

Lead and grow a data science team to deliver predictive and ML-driven insights. Partner with business and engineering to build production-ready models, enforce model governance, ensure explainability, and measure business impact while driving continuous improvement.

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.

Design, code, and enhance custom software components using modern frameworks and agile practices. Apply data science and machine learning techniques, process large datasets, improve performance, document changes, and mentor junior team members while collaborating with cross-functional teams.

Lead cross-functional teams to define and execute product strategy for the Service (Fixed Ops) portfolio. Ship AI-native agents and ML-powered features, partner with Data Science and Engineering to productionize trustworthy AI, own KPIs and commercial cases (pricing, packaging, ARR), improve the PDLC across scheduling, repair orders, warranty, invoicing and customer communication, and manage and mentor a team of product managers.

Lead the application of optimization techniques on large datasets, collaborate with engineering to deploy solutions, and manage project teams while contributing to data science capabilities and thought leadership.

Develop production-ready AI/ML applications using cloud AI services and generative models. Design and implement ML pipelines, work on deep learning, chatbots, and image processing, collaborate cross-functionally, lead and mentor team members, and improve processes for scalable deployment.

Design and model application data structures, storage, and integrations. Define data requirements, ensure data integrity and accessibility, support data governance, and collaborate with stakeholders to translate requirements into data solutions.

Designs and implements production-ready AI/ML applications using cloud AI services and generative models. Acts as SME, leads teams, mentors juniors, and improves ML pipelines, deep learning, and image-processing solutions while handling large datasets and feature engineering.