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Tier-1 brand, popular data-analyst title, and broad analytics skillset increase applicant competition.
Strong pharmaceutical and US commercial data requirements limit cross-industry transferability.
Explicit 1–2 years plus mandatory SQL and US healthcare dataset expertise enforces moderate filters.
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Own and maintain business rules for commercial and digital datasets ensuring accuracy, consistency, and compliance with data standards.
Collaborate with cross-functional teams to design and develop data products, support data ingestion, validation, and integrate commercial healthcare datasets (e.g., claims, sales, payer data).
Apply SQL, Python, and BI tools (Power BI, Tableau) to explore datasets, generate insights, maintain dashboards, and support automation and data governance across commercialization analytics.
Bachelor's or Master's degree in Data Science, AI, Engineering, or related field preferred.
1–2 years of experience in a Data Analyst or similar role, preferably in healthcare or pharma industry.
Proficiency in SQL required; working knowledge of Python; experience with BI tools like Power BI or Tableau.
Exposure to US healthcare commercial datasets such as claims, sales, or prescriptions.
Experience working with US commercial real-world healthcare data relevant for analytics.
Capable of managing cross-functional collaboration and multiple projects involving data engineering, forecasting, and commercial teams.
Familiarity with data platforms such as Databricks, Redshift, or Snowflake and interest in leveraging scalable frameworks and GenAI tools for automation.