Senior Data Scientist

Veeva Systems•Massachusetts - Boston, MA

5d•Remote

About The Position

Veeva Systems is a mission-driven public benefit corporation and a pioneer in industry cloud software for life sciences. As a Data Scientist on the Link Key Accounts team, you will develop models and methodologies that transform multi-source healthcare data into reliable intelligence about healthcare organizations, their networks, and decision-makers. The work includes quantitative analysis of claims and financial data as well as qualitative inference, such as constructing organizational charts and mapping influence from titles, roles, and other signals. This is an early, high-autonomy role with an opportunity to shape both the methods and the product. You will work with Product, Data Engineering, Engineering, and QA to move solutions from prototype into production and continue improving them. Veeva is a Work Anywhere company, supporting work from home or in an office. The role offers a base salary range of $95,000–$175,000 and may also be eligible for variable bonus and/or stock bonus. Actual salary depends on experience, location, qualifications, and expected contributions. The hiring process includes an application and third-party personality assessment, followed by a hiring manager conversation, practical case exercise, and final conversation with a senior leader if selected to interview.

Requirements

At least 5 years of hands-on data science and statistics experience.
At least 5 years working with healthcare data and the U.S. healthcare system.
Experience with healthcare claims data (medical and/or pharmacy) and metrics derived from it.
Experience with healthcare organizational data, including HCO/HCP, IDN, GPO, and payer data.
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, including cleansing, experiment design, solution assessment, and scaling.
Comfort with ambiguity and the ability to turn goals into tangible work plans.
Ability to explain statistical and technical concepts to audiences with varying levels of technical knowledge.

Nice To Haves

M.S. in Statistics, Computer Science, Machine Learning, Mathematics, or another quantitative discipline.

Responsibilities

Apply statistical and machine learning techniques to healthcare claims and other structured data to develop metrics and methodologies, such as readmission and average-length-of-stay calculations, all-payer estimates, and clinical ontologies.
Transform public financial data into clear signals and coherent assessments of healthcare organizations’ financial health.
Develop entity resolution and record-linkage models across health systems, provider organizations, employers, and payers.
Infer affiliations and map networks, including how organizations and people connect and how influence and reporting structures flow.
Infer organizational structures from qualitative signals and build organization charts and decision-maker maps from titles, positions, and role characteristics.
Design data-sourcing methodologies to evaluate, score, and combine heterogeneous inputs, including public filings, web sources, and licensed data, into accurate and defensible account signals.
Build models for account targeting and segmentation, including deciling, patient-volume and disease-state signals, and strategic filters.
Partner with Product, Data Engineering, Engineering, and QA to move solutions from prototype to production and then iterate and enhance them.