Senior Data Scientist – Real World Data & Healthcare Analytics
Location: Gurugram | Bangalore | Hyderabad | Pune | Navi Mumbai | Mohali | Panchkula
Work Model: Full-Time | Onsite
Shift: US/EST Aligned Working Hours (Night Shift)
Compensation: Up to ₹32 LPA
About the Role
We are looking for an experienced Data Science professional with strong expertise in Real-World Data (RWD), Healthcare Analytics, and observational healthcare research to support high-impact analytics initiatives for global healthcare and pharmaceutical programs.
The role involves working with large-scale healthcare claims and patient-level datasets to generate meaningful evidence supporting clinical, commercial, and strategic decision-making.
Key Responsibilities
- Perform advanced analytics on healthcare claims, patient journeys, treatment pathways, and longitudinal healthcare datasets.
- Develop statistical and machine learning models to support healthcare outcomes research and business decision-making.
- Design and execute observational studies, cohort analyses, and comparative effectiveness research initiatives.
- Work closely with Medical Affairs, HEOR, Market Access, Clinical, and Commercial teams to translate business questions into analytical solutions.
- Build scalable data pipelines, reusable analytical frameworks, and automated reporting workflows.
- Conduct feature engineering, cohort identification, survival analysis, predictive modeling, and longitudinal patient analytics.
- Interpret healthcare coding systems and structured clinical datasets to derive actionable insights.
- Present analytical findings to technical and business stakeholders using dashboards, storytelling, and visualization techniques.
- Maintain high standards for data quality, reproducibility, documentation, and analytical rigor.
Required Skills & Experience
- 4+ years of experience in Healthcare Analytics, RWE/RWD Analytics, Biostatistics, Pharmacoepidemiology, or related domains.
- Strong hands-on experience working with large healthcare claims datasets such as Optum, MarketScan, Medicare/Medicaid, EHR, or similar real-world data sources.
- Expertise in Python, R, SQL, SAS, or a combination of these technologies.
- Strong understanding of observational study methodologies, healthcare analytics, and patient-level longitudinal analysis.
- Experience with survival analysis, regression modeling, cohort creation, causal inference, propensity score matching, or related statistical methods.
- Familiarity with healthcare coding standards such as ICD-10, CPT, HCPCS, NDC, or LOINC.
- Experience working in cloud/distributed analytics environments including Spark, Fabric, Databricks, or similar platforms.
- Strong communication and stakeholder management capabilities.
Preferred Background
- Prior experience supporting pharmaceutical, biotech, healthcare consulting, or life sciences organizations.
- Exposure to Oncology, Hematology, Dermatology, Immunology, or other complex therapeutic areas.
- Experience contributing to publications, conference abstracts, HEOR studies, or evidence-generation initiatives.
- Knowledge of healthcare economics, market access analytics, or commercialization analytics is a plus.
