Senior Manager, Data Scientist SME

We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready.

We offer accelerated, global growth opportunities for talent that is bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it?

We understand that you are looking for growth and variety in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you.

We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology.

We offer global opportunities with fast-track careers while you work with a team that is fueled by purpose. The combination of these will lead to a truly differentiated experience for you. If this excites you, then apply below.

Locations : Bangalore, Pune, Mumbai, Gurgaon, Hyderabad Senior Manager, Data Scientist SME Domain Expertise - Strong expertise in advanced analytics, machine learning, statistical modeling, and end‑to‑end data science delivery.

• Deep understanding of pharma and healthcare data ecosystems, including RWE, RWD, EMR/EHR, claims, registry, patient support, medical/scientific data, and clinical operations datasets.
• Experience with medical affairs, commercial analytics, HEOR, safety analytics, or clinical analytics domains.
• Skilled in working with structured, semi‑structured, and unstructured scientific/medical data.
• Hands‑on experience with data engineering pipelines, model development, validation, and deployment in production environments.
• Exposure to Generative AI/LLMs, NLP, embeddings, vector search, and large‑scale text mining for medical/scientific use cases.

You will be responsible for: Data Science & Advanced Analytics - Leading the design, development, and implementation of machine learning, statistical, and AI‑driven models for pharma and healthcare use cases.

• Building advanced NLP, GenAI, and text mining pipelines for literature analysis, medical content generation, signal detection, and insight extraction.
• Domain Leadership
• Acting as a Subject Matter Expert (SME) for data science in pharma — guiding scientific rigor, methodology selection, and analytical interpretation.
• Translating complex healthcare business problems into structured analytical frameworks and data science solutions.
• Providing deep domain consultation across medical affairs, commercial, clinical, and RWE teams. Data Strategy, Quality & Governance - Partnering with cross‑functional teams (data engineering, medical SMEs, product, AI teams) to build scalable data pipelines and analytical architectures.
• Ensuring high standards of data quality, modeling accuracy, compliance, and reproducibility across all projects.
• Leading analytical governance frameworks, performance tracking, validation cycles, and continuous model improvement. Client & Stakeholder Management - Working closely with global pharma clients to shape analytical roadmaps, define business problems, and present insights.
• Supporting proposals, solutioning, capability pitches, and thought leadership initiatives. Innovation & Emerging Technology - Driving innovation in GenAI adoption in data science, leveraging LLMs for structured/unstructured medical data transformation.
• Experimenting with next‑generation techniques including multimodal models, knowledge graphs, and AI‑powered reasoning frameworks.

Your Impact: About You - Master’s or PhD in Data Science, Statistics, Computer Science, Engineering, Bioinformatics, or Life Sciences with strong analytical focus.

• 8–15 years of experience as a Data Scientist with significant work in pharma, biotech, life sciences, or healthcare analytics.
• Proven experience in building scalable analytics or AI solutions for healthcare datasets.
• Deep understanding of pharma workflows, scientific data, medical affairs, commercial analytics, or clinical development processes.
• Strong programming skills in Python, R, SQL, and experience with frameworks like Scikit‑learn, TensorFlow, PyTorch, Spark, Databricks, MLflow, etc.