Senior Data Analyst, Pharmaceutical Industry

Job Description: Senior Data Analyst, Pharmaceutical Industry Job Details : 90% remote position in the United States, FT Perm W2 employee Travel Requirements: up to 10% domestic travel each year for company events and socials Time Zone Preference: US East Coast Role Purpose: The Senior Data Analyst supports pharmaceutical brand, commercial (marketing), and analytics teams by playing a critical technical role connecting healthcare data to media to drive clear, actionable insights. This role requires strong technical analytics skills, rigorous statistical thinking, and the ability to communicate findings in a simple, compelling way to both technical and non-technical stakeholders within the company. The ideal candidate is articulate, collaborative, detail-oriented, and comfortable working with imperfect data and complex data structures to enable advanced analysis, including AI and machine learning applications. Core Responsibilities: Perform extensive SQL-based data transformations , integrating data from multiple internal and external sources (e.g., claims, media, CRM, EHR-derived datasets). Define, validate, and govern metrics aligned to pharmaceutical business questions (e.g., brand performance, HCP engagement, patient journeys). Apply statistical reasoning to analyze trends, identify drivers of performance, and ensure analytical rigor in insights and recommendations. Support AI data modeling and machine learning initiatives by preparing, validating , and structuring scalable datasets in collaboration with data science and technology teams. Maintain and iterate on analytical datasets and workflows as new data is ingested. Conduct thorough exploratory data analysis (EDA) to uncover patterns, anomalies, and opportunities within complex healthcare datasets. Interpret and translate analytical findings into clear business insights , tailored for stakeholders across marketing, analytics, strategy, and leadership teams. Manually scrub, structure, and normalize data as needed to ensure data quality and analytical readiness, particularly for deep-dive analyses. Prepare datasets to support advanced analytics, including exploratory and explanatory machine learning techniques, ensuring accuracy, consistency, and scalability. Develop data visualizations and dashboards that clearly communicate insights and support decision-making. Collaborate cross-functionally with data science, technology, media, strategy, and client-facing teams to align analyses with business needs. Document methodologies, assumptions, and data limitations to support transparency and reproducibility. Cross-functional Interfaces: Strategic Solutions Data & Technology Success Indicators (What good looks like): Bachelor’s degree or equivalent work experience Experience working with cloud data warehouses ( e.g., Big Query). Demonstrated hands-on experience developing, testing, and refining AI models and machine learning solutions to address business and analytical needs. Strong proficiency in SQL , including complex joins, transformations, and performance optimization. Solid foundation in statistics and analytical reasoning (e.g., trend analysis, hypothesis testing, segmentation). Demonstrated experience with exploratory data analysis and working with large, complex datasets. Ability to simplify complex data and insights for diverse audiences. Experience with data visualization tools (e.g., Tableau, Power BI, Looker, or similar). Proven ability to work collaboratively in cross-functional teams. Preferred Qualifications Experience working with pharmaceutical commercial or media data (e.g., claims, prescription, media, CRM, hub data). Familiarity with AI/ML concepts and data preparation requirements for modeling. Experience using Python or R for analytics and data manipulation. Understanding of pharma compliance, privacy, and data governance considerations. Experience working in a remote setting , collaborating cross-functionally with individuals across teams and in differe…