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Strong employer brand, metro location, and popular Data Analyst title increase applicant competition.
Requires domain-specific US commercial healthcare data knowledge, making cross-industry transferability limited.
Explicit 1–2 year requirement plus mandatory SQL and healthcare dataset experience enforces moderate filtering.
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Own and maintain business rules for commercial and digital datasets ensuring accuracy and alignment with data standards.
Collaborate with cross-functional teams to design and support scalable data products and analytics solutions across commercialization.
Use SQL and Python to analyze pharma datasets, generate insights, maintain dashboards, and support data integration and governance activities.
Bachelor's or Master's degree in Data Science, AI, Engineering, or related discipline.
1-2 years of experience as Data Analyst or similar role, preferably in healthcare or pharma industry.
Proficiency in SQL is required; basic Python skills for data extraction and analysis.
Exposure to US commercial real-world data sources (claims, sales, payer datasets).
Experienced with healthcare or US commercial pharma data sources and analytics use cases.
Able to manage multiple projects and collaborate effectively with cross-functional teams involving data engineering and therapeutic stakeholders.
Skilled in applying analytical techniques and building dashboards using BI tools like Power BI or Tableau, with some familiarity or hands-on experience in data platforms (Databricks, Redshift, Snowflake) preferred.