Top Data Scientist Jobs in Pune

Drives growth through complex, high-value sales opportunities across data, analytics, AI, and SaaS solutions. Owns the full sales cycle, expands executive stakeholder networks, supports strategic renewals, leads workshops, and communicates measurable customer value. Partners with account managers and cross-functional teams in enterprise, academic, and government environments. Extensive regional travel and engagement with senior stakeholders are required.

Drives strategic sales growth across data, analytics, AI, and SaaS solutions for academic, government, and enterprise accounts. Owns complex opportunities through the full sales cycle, expands executive stakeholder networks, supports high-value renewals, leads workshops, and communicates measurable customer value. The role requires strong commercial judgment, technical fluency, senior-level presentation skills, cross-functional collaboration, and extensive regional travel.

Drive full-cycle sales for complex, high-value AI research workspace opportunities. Originate and close new business, support strategic renewals, expand stakeholder relationships, lead value-based workshops, and translate AI and research analytics capabilities into measurable customer outcomes. Engage senior decision-makers across enterprise, government, academic, and research organizations while developing pipelines, territories, business cases, negotiations, and long-term account growth.

Owns the full sales cycle for complex, high-value AI research workspace opportunities, from prospecting and discovery through negotiation and closure. Builds executive stakeholder relationships, generates new business, supports strategic renewals, leads workshops, develops business cases, and communicates measurable value from AI-powered research and knowledge workflow solutions. Requires enterprise sales expertise, AI fluency, consultative selling skills, and extensive regional travel.

The Data Science Manager will lead AI/ML solution development for clients in Supply Chain & Manufacturing, mentor data scientists, and drive business development efforts.

Leads data science teams supporting commercial healthcare analytics, translating business needs into analytical problems and production-grade ML and GenAI solutions. Responsibilities include defining technical requirements, developing models, applying GenAI, managing end-to-end projects, collaborating with stakeholders, presenting insights to executives, mentoring data scientists, and building expertise in oncology analytics, patient-level data, HCP analytics, and segmentation.

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.

Develop and deliver pharmaceutical forecasts and analytical solutions using statistical and ML techniques. Collaborate cross-functionally to build assumptions, automate and improve forecasting processes, communicate findings to stakeholders, and maintain documentation and forecasting tools.

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.

The Senior Product Manager will drive product strategy and development, collaborating with cross-functional teams to enhance customer experience, focusing on AI and SaaS solutions.

Build governed Databricks Lakehouse foundations and productionize machine learning and GenAI solutions, including forecasting, anomaly detection, NLP, RAG, and predictive analytics. Develop reliable batch and streaming workflows, CI/CD, monitoring, governance, security, lineage, and semantic models. Collaborate with product, data, platform, and domain teams to deliver measurable customer value while meeting reliability, compliance, cost, and operational objectives.

The role involves conducting AI research, teaching AI-related courses, collaborating on healthcare data modeling, and securing external funding, while mentoring students.

Develops production-grade data science solutions using statistical modeling, machine learning, causal inference, and experimental design. Responsibilities include data exploration, feature engineering, model validation, deployment packaging, explainability, model documentation, experiment tracking, and production pipeline collaboration. The role focuses on fraud and risk, predictive maintenance, and patient outcome modeling, while mentoring junior analysts and translating research into platform capabilities.

Leads data science and machine learning architecture engagements, analyzing diverse datasets and deploying models using cloud and big data technologies. Designs scalable, cost-effective solutions, including generative AI applications, and provides technical leadership across client delivery and presales activities. Creates standards, accelerators, reports, and presentations; mentors junior staff; and communicates technical concepts to business stakeholders.

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.

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.

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.

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.

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

The Principal Engineer, Data Science role involves leading data science projects and providing strategic insights using extensive IT experience.

Lead AI and data innovation by developing ML models, optimizing data systems, and mentoring junior team members in a collaborative team environment.

Lead post-deployment operations and optimization of Agentic AI, LLM integrations, and Python-based analytical pipelines. Supervise a data science operations team, ensure secure high-availability production systems, manage integrations with enterprise systems (SAP, Salesforce, Postgres), and drive continuous improvement, monitoring, and adoption of analytics solutions.

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