Senior Data Analyst

Veeva Systems is a mission-driven industry cloud company helping life sciences organizations bring therapies to patients faster. The Senior Data Analyst will develop statistical and machine learning models that transform healthcare, financial, and organizational data into reliable intelligence, including account signals, network maps, and decision-maker insights. The role partners with cross-functional teams to move solutions from prototype to production.

Responsibilities:

• Apply statistical and machine learning techniques to healthcare claims and other structured data to build new metrics and methodologies — for example, calculating readmissions and average length of stay across varied claims sources, producing all-payer estimates, and developing clinical ontologies
• Transform public financial data into clear signals and a coherent story about the financial health of healthcare organizations
• Build entity resolution and record-linkage models across health systems, provider organizations, employers, and payers
• Develop affiliation and network mapping — inferring how organizations and people connect, and how influence and reporting structures flow across them
• Infer organizational structure from qualitative signals, building org charts and decision-maker maps from titles, positions, and role characteristics
• Design data-sourcing methodologies that evaluate, score, and combine heterogeneous inputs (public filings, web sources, licensed data) into accurate, defensible account signals
• Build the models that power account targeting and segmentation — deciling, patient-volume and disease-state signals, strategic filters
• Partner with Product, Data Engineering, Engineering, and QA to take solutions from prototype to production, then iterate and enhance

Requirements:

• 5+ years of hands-on data science and statistics experience
• 5+ years working with healthcare data and the US healthcare system
• Experience with healthcare claims data (medical and/or pharmacy) and the metrics derived from it
• Experience with healthcare organizational data (HCO/HCP, IDN, GPO, payer)
• Experience developing clinical ontologies or standardized healthcare data models
• Experience with entity resolution, record linkage, or fuzzy matching on real-world, imperfect data
• Track record of inferring structure from noisy, incomplete data - cleansing, experiment design, solution assessment, and scaling
• Comfortable with ambiguity and turning goals into tangible work plans
• Able to explain statistical and technical concepts to audiences of varying technical depth
• M.S. in Statistics, Computer Science, Machine Learning, Mathematics, or another quantitative discipline