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# Data Scientist

- **Company:** Veeva Systems
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $95,000.0 - $140,000.0
- **Contract:** Permanent contract
- **Skills:** Information Engineering, Machine Learning, Information Technology
- **Published:** July 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f42caf2a2b7aebdc

## About the Role

* 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

## Description

As a Data Scientist on the Link Key Accounts team, you'll build the models and methodologies that turn multi-source healthcare data into reliable intelligence about healthcare organizations, their networks, and the people who make decisions inside them. The work spans both ends of the spectrum: quantitative analysis of claims and financial data, and qualitative inference - building org charts and mapping influence from titles, roles, and other soft signals. This is an early, high-latitude role with room to shape both the methods and the product., * 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


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