Top Data Science Jobs in Mumbai

Lead and mentor a multidisciplinary engineering and data science team to design, build, and operate scalable data collection pipelines and AI/ML systems. Provide technical oversight on NLP, LLMs, generative AI, MLOps, and unstructured data processing. Collaborate cross-functionally to align solutions with business goals, ensure system reliability, security, and compliance, and drive hiring and process improvements.

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.

Drive enterprise sales growth across India by generating new business and expanding strategic accounts. Sell complex HR, L&D, assessment, and analytics solutions to C-suite buyers, advise on workforce transformation, collaborate cross-functionally, forecast using data, and represent the company at industry events. Manage long, multi-stakeholder deals and travel up to 40%.

The VP, SEO will architect and scale SEO practices, drive organic search innovation, enhance tools, and lead strategic growth for Tier 1 clients, focusing on AI and GEO.

Lead product strategy and roadmap for Compass, an in-store navigation and personalization product. Collaborate with engineering, data science, design, and analytics to define data models, optimize recommendation models, run experiments (A/B, DiD), and deliver personalized experiences that improve associate and customer item discovery and business metrics.

Lead regional GenAI product strategy and commercialization across Ascend and Fraud portfolios. Drive discovery, productization, scaling, and adoption of GenAI features; partner with Engineering, Data Science, Sales and GTM; ensure governance, explainability, and measurable commercial outcomes.

Lead delivery of scalable intelligent automation and agentic AI solutions for Finance: own product portfolio, identify/prioritize use cases, manage end-to-end delivery, realize value metrics, lead team and vendors, and ensure governance, scalability, and enterprise alignment.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Lead enterprise data & AI architecture for strategic clients: support account planning, seed and execute opportunities, design multi-domain analytics solutions, run C-suite workshops, orchestrate technical architects, ensure data modeling, governance and cost-value optimization, and drive bookings KPI.

Lead design and delivery of end-to-end AI/ML and Generative AI solutions, architect scalable cloud-based platforms, integrate LLM/RAG/agentic systems, implement MLOps and governance, and mentor teams while driving AI strategy with stakeholders.

Build and maintain scalable analytics infrastructure and predictive models; define analytics roadmap; run experiments for acquisition, churn, delinquency and profitability; create dashboards and automated reports; monitor model and business performance; ensure data accuracy and partner with cross-functional teams.

The Product Owner is responsible for the product vision, roadmap, and stakeholder alignment in delivering enterprise data products. This includes managing backlogs, ensuring product adoption, establishing governance, and maintaining high-quality standards.

The Data Scientist will analyze and model data for ML systems, focusing on Personalization and Recommendation Engines, and collaborate with teams to enhance data-driven solutions.

As an Associate Product Manager, you will manage product development cycles, collaborate with engineering and operational teams, evaluate partnerships, and prioritize projects to improve customer adoption.

Lead design, development, and deployment of AI/ML solutions for sustainability, ESG, and H&S. Hands-on agent and LLM/BERT development, architect enterprise-grade systems, manage end-to-end ML lifecycle (data strategy, MLOps, production), advise senior clients, mentor teams, and ensure responsible AI, governance, and scalability.

Design, develop, and deploy enterprise AI/ML solutions including GenAI, LLM-based RAG systems, and agentic AI. Build scalable models, integrations, monitoring, and reusable frameworks while collaborating with stakeholders for production adoption and continuous improvement.

Lead design and delivery of NLP and Generative AI solutions, from problem definition through deployment. Build and fine-tune transformers and LLMs for summarization, QA, classification and chatbots, apply classical and deep learning methods, ensure scalable reproducible ML workflows in cloud environments, mentor junior data scientists, and collaborate with product and engineering to translate business problems into AI solutions.

Design, develop, and deploy scalable AI/ML and Generative AI solutions (LLMs, RAG, agentic AI). Build AI agents, create intelligent workflows, fine-tune and monitor models, integrate with enterprise systems, and support production deployment and continuous improvement.

The role involves leading data science initiatives, mentoring team members, deploying models, and ensuring high-quality technical solutions. Responsibilities include coding, architecture design, and client requirement translation.

The role involves analyzing data to drive strategic decisions and improve employee benefits services. Requires strong analytical skills and experience in data science.

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 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 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 Senior Staff Engineer, Data Science role involves guiding team direction, solving complex challenges for clients, and leveraging technical expertise to innovate solutions.