Lead Data Scientist, Causal Inference & Clinical Outcomes Contractor (Bolingbrook, IL)

The role

The Lead Data Scientist will lead the design and execution of clinical outcomes studies to evaluate the effectiveness of healthcare programs. This person will apply causal inference methodologies to analyze healthcare claims and EHR data to quantify clinical and financial outcomes.

What you will do

• Lead the development and execution of longitudinal, quasi-experimental clinical outcomes studies.
• Evaluate the effectiveness of APCM and CCM programs using healthcare claims and EHR data.
• Establish patient cohorts, comparison groups, outcome definitions, and analytical frameworks.
• Quantify differences in hospitalization rates, readmissions, and post-discharge follow-up outcomes.
• Apply advanced causal inference techniques to estimate the impact of healthcare interventions.
• Utilize methodologies such as propensity score matching, inverse probability weighting, and difference-in-differences.
• Analyze complex healthcare claims, EHR, and patient utilization datasets.
• Develop and maintain analytical workflows using Python, R, and SQL.
• Collaborate with the Director of Business Intelligence and other internal stakeholders.
• Review and assess analytical deliverables produced by previous external vendors.

Required qualifications

• Extensive professional experience in data science, biostatistics, epidemiology, health economics, or clinical outcomes research.
• Demonstrated expertise in causal inference and observational study design.
• Proven experience evaluating healthcare interventions and measuring clinical outcomes.
• Strong proficiency in Python, R, and SQL.
• Experience analyzing large-scale healthcare claims and EHR datasets.
• Deep understanding of propensity score matching, quasi-experimental research methodologies, statistical validation, and confounding adjustment.
• Ability to independently design and execute technically sophisticated analytical studies.
• Experience developing statistical methodologies suitable for rigorous clinical, actuarial, or external stakeholder review.
• Strong understanding of healthcare data privacy, HIPAA, and protected health information requirements.
• Excellent communication skills, including the ability to present complex findings to nontechnical stakeholders.
• Advanced degree in Statistics, Data Science, Biostatistics, Epidemiology, Health Economics, or a closely related quantitative discipline.

Nice to have

• Previous experience as a Health Economics and Outcomes Research (HEOR) Consultant, Principal Data Scientist, or Lead Biostatistician.
• Experience evaluating chronic care management, population health, value-based care, or Medicare-related programs.
• Familiarity with APCM, CCM, and healthcare reimbursement models.
• Experience working with healthcare actuaries or validating analytical methodologies for actuarial review.
• Knowledge of dbt, Amazon Redshift, and Looker.
• Experience supporting health-tech startups or rapidly growing healthcare technology companies.
• Strong consulting background with the ability to deliver results independently.
• Experience developing executive-level clinical outcomes presentations and client-facing research reports.

About the company

Jaan Health is an innovative, AI-powered healthcare technology company focused on transforming proactive care management and improving patient outcomes. Through its proprietary Phamily platform, Jaan Health enables healthcare providers to deliver scalable, high-quality care management services.