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Tier-1 brand and metro location increase applicants, but niche pharma analytics and IQVIA expertise narrow the pool.
Role requires pharma-specific datasets (IQVIA, claims, EMR) and healthcare analytics experience, limiting cross-industry transferability.
Multiple explicit years requirements and mandatory PySpark/Python/DataBricks and IQVIA experience create strict screening filters.
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Translate complex healthcare and pharma real-world data into actionable insights to influence commercial brand strategy and market execution.
Develop and deploy advanced statistical models, machine learning, and scalable data pipelines (using PySpark and DataBricks) to analyze large longitudinal datasets including claims and EMR.
Communicate findings via visualizations and dashboards (PowerBI, Tableau, etc.) to inform resource allocation, performance measurement, and strategic decisions in oncology and pharma launches.
Bachelor’s degree in Quantitative field (Engineering, Operations Research, Econ, Statistics, Applied Math, CS or Data Science) is mandatory; advanced degree preferred.
2+ years experience in Pharmaceutical/Biotech/Healthcare analytics or secondary data analysis; 5+ years applying advanced statistical methods on large datasets.
4+ years experience with PySpark, Python, R, SQL; familiarity with DataBricks platform.
Proven ability handling and analyzing large secondary longitudinal datasets (Claims, EMR); experience with IQVIA data sets is required.
Experienced in advanced statistical methodologies: Design of Experiments, Time Series, Regression, Bayesian methods, Econometrics, Predictive Modeling and Simulation.
Demonstrated capability to partner with commercial leadership and cross-functional teams to influence strategy and resource prioritization through data.
Strong expertise building scalable, reproducible analytics solutions and communicating complex insights clearly using BI tools for high-impact business decisions.