Senior Data Scientist

Responsibilities

• Design and execute causal analyses of real-world health data to quantify the impact of medications and interventions on patient outcomes and costs
• Develop, validate, and deploy predictive and causal models and AI tools into Arine's medication management platform
• Partner with clinicians and HEOR researchers to frame questions as well-defined causal estimands
• Create presentations and reports communicating methods, assumptions, and results to cross-functional stakeholders
• Participate in critical reviews within the Data Science team on methods, study design, and implementation strategy

Requirements

• Master's or PhD in Statistics, Biostatistics, Epidemiology, Health Economics, Computer Science, or a related quantitative field
• Expertise in causal modeling with observational data (e.g., propensity score methods, instrumental variables, difference-in-differences)
• Hands-on experience with causal machine learning methods (e.g., double machine learning, causal forests, TMLE)
• 3+ years of experience working with real-world healthcare data (medical/pharmacy claims or EHR)
• Proficiency with R, Python (scikit-learn, pandas, numpy), and SQL
• Ability to pass a background check
• Must live in and be eligible to work in the United States

Preferred Qualifications

• Experience modeling cost-of-care outcomes in high-risk populations
• Deep experience with advanced difference-in-differences and quasi-experimental designs
• Productive use of AI-enhanced coding tools
• Familiarity with survival analysis and longitudinal methods
• Experience deploying models into commercial software products

About the Company

Arine is a rapidly growing healthcare technology and clinical services company dedicated to ensuring individuals receive the safest and most effective treatments through a specialized SaaS platform combining data science, machine learning, and clinical expertise.