Senior Business Analyst analyzing multi-source datasets and leveraging insights to influence decisions. Requires strong analytical techniques and expertise in patient-level data analytics.
Responsibilities
Drive high-impact insights through rigorous analysis and visualization of large, complex, and multi-source datasets
Lead the structuring of ambiguous business questions into clear, hypothesis-driven analytical problems, defining business rules, process flows, and end-to-end methodologies
Apply advanced statistical and analytical techniques to test hypotheses, quantify impact, and support strategic decision-making
Own data preparation and analytical rigor, including data wrangling, quality assurance, triangulation across sources, and validation of results
Take full accountability for delivery of ad-hoc and recurring analytical workstreams, managing timelines, dependencies, and quality independently
Synthesize complex analyses into sharp, insight-led narratives and executive-ready deliverables with clear implications and recommendations
Act as a thought partner to senior team members during client engagements by developing analyses, exhibits, and defensible storylines that influence client decisions.
Requirements
2+ years of professional experience in Sales/Field analytics or Health Equity
Must be well versed with MS Excel, Word and PowerPoint
Strong hands-on experience with SQL and Pyspark
Good to have – Python, Dataiku, any visualization tool (Tableau, Qlik)
Patient-level data analytics using real-world data (RWD) sources, including IQVIA APLD, IQVIA LAAD, Symphony Claims or Komodo Health Claims
Market and sales analytics using IQVIA/IMS datasets, including MIDAS and U.S. EDI sales feeds (e.g., 867/852), to assess market size, growth, and competitive dynamics
HCP engagement and interaction analytics using CRM activity data, such as Veeva interactions, to assess field force activity, reach, and engagement effectiveness
Health Equity or Socioeconomic (SES) driven analysis using U.S. Census and demographic datasets, integrated with patient- and market-level data to understand population characteristics and disparities.
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