Seeking an experienced Data Scientist with strong Real-World Evidence (RWE) expertise to work on healthcare and pharma analytics projects. The role involves designing and executing observational studies, analyzing large healthcare claims datasets, applying advanced statistical methodologies, and delivering actionable insights for medical, regulatory, and commercial decision-making.

Responsibilities

- Design and execute end-to-end observational and RWE studies.
- Develop study protocols, feasibility assessments, and statistical analysis plans (SAPs).
- Analyze large patient-level healthcare claims datasets including Optum, IBM MarketScan, Medicare/Medicaid, and similar sources.
- Build analysis-ready cohorts, clinical outcomes, and reusable data assets from raw healthcare data.
- Apply advanced statistical techniques including regression modeling, survival analysis, longitudinal analysis, propensity score methods, and covariate adjustment.
- Build scalable and reproducible analytics pipelines using Python, R, SQL, Spark, Databricks, Snowflake, or similar cloud platforms.
- Collaborate with medical affairs, HEOR, market access, regulatory, and business stakeholders.
- Translate complex analytical findings into explicit client-ready reports, presentations, and insights.
- Support scientific publications, conference abstracts, and evidence-generation initiatives.




- Stay updated with evolving RWE methodologies and FDA/EMA regulatory guidance.

Required Skills Python R SQL RWE Healthcare Claims Data Optum MarketScan Medicare/Medicaid Statistical Analysis Regression Modeling Survival Analysis Longitudinal Analysis Propensity Scoring Spark Databricks Snowflake Cloud Analytics Data Pipelines Healthcare Analytics Biostatistics

Preferred Skills

- Experience supporting HEOR, medical affairs, market access, or regulatory submissions.
- Knowledge of causal inference methods including instrumental variables, difference-in-differences, and target trial emulation.
- Experience in oncology, dermatology, immunology, hematology, or related therapeutic areas.
- Experience contributing to peer-reviewed publications or scientific conference abstracts.
- Strong communication, presentation, and stakeholder management skills.
- Education: Bachelor s degree in Statistics, Data Science, Computer Science, Mathematics, Public Health, or a related quantitative field. Master s degree or certifications in Epidemiology, Biostatistics, or Health Informatics are a plus.

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📌 Data Scientist (India)
🏢 Neotechie
📍 India