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Tier-1 employer, metro location, mid-level generalist analytics role, and broad SQL/Python/BI requirements increase competition.
Core SQL/Python/BI skills are transferable but pharma managed-markets and claims datasets require domain-specific experience.
Explicit years-by-qualification bands plus mandatory SQL/Python/BI skills and pharma preferred experience enforce strict filters.
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Lead development of dashboards, reports, and data models using pharmaceutical commercial datasets across multiple therapy areas including Oncology and Rare Disease.
Analyze large healthcare datasets using SQL and Python to deliver actionable payer, reimbursement, and access insights supporting commercial performance.
Collaborate with global stakeholders to translate business questions into analytical solutions and present clear, business-ready recommendations leveraging AI-enabled tools.
Proficiency in SQL with experience handling large datasets using joins, aggregations, CTEs, window functions.
Intermediate Python skills for data analysis and automation.
Strong experience with BI tools such as Power BI or Tableau, including dashboard and KPI development.
Education: Master’s (1-3 years experience), or Bachelor’s (3-5 years), or Diploma (7-9 years) in analytics, BI, CS, stats, data science, engineering, economics, pharmacy, life sciences, or related.
Work Experience Required: 1 to 9 years depending on education level.
Experienced in pharmaceutical/healthcare analytics with understanding of US pharma ecosystem: payers, PBMs, IDNs, formulary, claims, reimbursement.
Demonstrated ability to handle complex datasets, build scalable analytics frameworks, and communicate insights effectively to global stakeholders.
Comfortable adopting AI-enabled analytics tools to enhance productivity and insight quality in a dynamic environment.