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Tier-1 brand, mid-level generalist data skills, metro location, and broad toolset requirements increase competition.
Requires pharma-specific datasets and IQVIA experience, making industry background highly relevant.
Multiple explicit years and mandatory technical/domain skills (PySpark, Python, SQL, Databricks, pharma data) make screening strict.
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Drive strategic and operational excellence within the Commercial Organization by acting as an internal consultant to a brand team, creating commercial solutions for data-driven decisions.
Lead development and deployment of new analytic capabilities, collaborating with cross-functional teams including Marketing, Sales, Medical, and Market Access to sustain competitive advantage.
Summarize and present analytical findings through various channels to influence impactful business decisions and foster use of customer insights in strategy.
Bachelor's degree in quantitative field such as Engineering, Operations Research, Economics, Statistics, Applied Math, Computer Science, or Data Science (advanced degree preferred).
2+ years of experience in Pharmaceutical / Biotech / Healthcare analytics or secondary data analysis.
5+ years experience applying sophisticated statistical methods on large disparate datasets; 4+ years proficiency with PySpark, Python, R, SQL.
Proficiency with MS Office (Excel, PowerPoint); experience handling large patient-level data sources such as Claims, EMR; experience with IQVIA data sets; proficiency with platforms like DataBricks.
Experienced in applying statistical analysis and modeling techniques including Build of Experiments, Time Series, Regression, Econometrics, and Bayesian methods, with data mining and predictive modeling skills.
Ability to collaborate with business leaders and cross-functional teams, effectively communicate insights, and influence commercial leadership.
Exposure to pharmaceutical brand analytics, familiarity with AZ brand and oncology domain is advantageous; experience with Big Data and Spark technologies preferred.