Associate Data Scientist
Role details
Job location
Tech stack
Job description
· Build, validate, and maintain analytic datasets from claims and other healthcare data sources; implement data quality checks and documentation
· Develop machine learning models and predictive analytics (e.g., trial prediction, cohort identification)
· Design and conduct analyses to generate insights from real-world data (e.g., patient journeys, adherence/persistence, provider patterns, line-of-therapy proxies)
· Partner with internal stakeholders to translate business and investment questions into technical workplans, and communicate results in a clear, actionable format
· Create repeatable workflows, codebases, and dashboards/notebooks that improve speed, rigor, and scalability of analysis
· Contribute to best practices around data governance, privacy-aware handling of sensitive datasets, and reproducible research
· Stay current on healthcare data methods, claims-based measurement approaches, and practical ML techniques relevant to real-world evidence
Requirements
Patient Square Capital ("Patient Square", "The Firm") is seeking an Associate Data Scientist to join the Patient Square Insights (PSI) team. Patient Square Insights is an in-house scientific, technical, and market research team that brings a diverse set of expertise to health care investing. This role will help build and maintain data pipelines and analytic datasets, develop machine learning models to support prediction and decision-making, and translate complex analyses into clear insights for internal stakeholders. The ideal candidate has 1-3 years of industry experience working with large health care datasets (especially claims), strong technical fundamentals, and a collaborative, results-oriented mindset., · BS/MS in a quantitative field (e.g., Computer Science, Statistics, Data Science, Applied Math, Engineering, Economics, or similar)
· Analytical requirements:
o 1-3 years of industry experience in data science, analytics, or related roles
o Strong programming skills in Python and R; experience with SQL and relational databases
o Experience building predictive models (e.g., classification, regression, time-to-event/survival, propensity modeling) and evaluating performance with appropriate metrics
o Familiarity with ML tooling and best practices (feature engineering, cross-validation, leakage prevention, model interpretability, reproducibility)
o Experience with data wrangling and large-scale dataset construction (pandas/PySpark or equivalent); comfort working in cloud environments is a plus (AWS/GCP/Azure)
o Strong problem-solving and analytical skills; ability to work with ambiguous questions and create structured approaches
· Healthcare experience is a strong plus. This could include:
o Hands-on experience working with healthcare claims data (e.g., medical and pharmacy claims), eligibility, and provider data; familiarity with common coding systems (ICD-10, CPT/HCPCS, NDC) is a plus
o Previous experience modeling clinical trial outcomes, interpreting clinical trials, and/or designing clinical trials
o Previous experience modeling EHR data to identify novel patient populations
· Professional requirements:
o Excellent written and verbal communication skills, including the ability to simplify and communicate technical results to non-technical audiences
o Team spirit and eagerness to collaborate in a fast-paced environment while managing multiple workstreams
Benefits & conditions
The expected annualized salary range for this role is $150,000-$200,000. Compensation for this role may also include a discretionary bonus, subject to Patient Square policies and individual and Firm performance. The actual salary offered will depend on factors such as relevant skills, experience, training, education, and job-related qualifications, as well as market and organizational considerations. This range represents the Firm's good-faith estimate at the time of posting. The salary range may be modified in the future as permitted by applicable law.
