Posted May 14, 2026
We are seeking an analytical powerhouse to redefine proactive healthcare as our Lead Data Scientist for Causal Inference & Clinical Outcomes. In this 16-week engagement starting May 7, 2026, you will lead a rigorous clinical outcomes study for our key client, Silver Cross Medical Group (SCMG), to quantify the impact of our Advanced Primary Care Management (APCM) and Chronic Care Management (CCM) programs. Your primary mission is to provide empirical evidence answering two critical questions: Do patients in our programs have lower hospital readmission rates and higher discharge follow-up rates?. This role requires a specialist who can manipulate complex healthcare claims and EHR data to build an airtight, actuarial-grade causal inference framework. Additionally, you will audit and extract value from a previous analytics vendor’s deliverables to close out their engagement. If you are a health-tech veteran who excels at translating complex statistical findings into compelling narratives for stakeholders, we want to hear from you. ### Key Responsibilities
Study Design & Execution: Lead a longitudinal, quasi-experimental study starting May 7 to measure clinical outcomes, specifically hospitalization frequency and discharge follow-ups. - Causal Inference Modeling: Apply advanced methodologies (e.g., propensity score matching) to observational data to estimate counterfactual patient outcomes with minimal bias. - Develop and refine statistical models that will be thoroughly vetted and approved by customer actuaries. - Serve as the primary analytical face to SCMG, gathering requirements and aligning on clinical/business definitions of success. - : Translate complex statistical findings into compelling presentations and client-ready reports for both technical and non-technical leadership. - Extract usable value from an existing outsourced study, close out the vendor contract, and integrate relevant findings into the final study. - Navigate and build analytics reporting infrastructure using SQL, Python, dbt, Redshift, and Looker. - Ensure all code is clean and reproducible for final handover to the internal Phamily BI team. ###
Health-Tech Expertise: Deep experience in causal inference, metric design, and clinical outcomes evaluation. - Data Proficiency: Extensive experience working with complex EHR and healthcare claims data. - Advanced Analytics Toolkit: Highly capable in Python, R, SQL, dbt, Redshift, and Looker. - Statistical Matching: Proven experience developing algorithms for high-dimensional statistical matching with large datasets. - Security Standards: Practical experience maintaining strict PHI security protocols while building data infrastructure. - Analytical Rigor: Ability to design and execute "actuarial-grade" studies that control for significant confounding variables. - Communication: Exceptional ability to synthesize technical data into narratives for non-technical clients. - Education: Advanced degree in a quantitative field (e.g., Data Science, Statistics, Health Economics, or Epidemiology). ### Preferred Requirements
Entrepreneurial DNA: A 'builder' mentality with the ability to operate effectively in high-ambiguity environments where processes may not be fully fleshed out. - HEOR Consulting: Prior background as a Health Economics & Outcomes Research (HEOR) consultant. - Actuarial Alignment: Experience in presenting methodology to and gaining approval from health system actuaries. ### Work Style & Logistics
This is a remote-first position. - The project is estimated to run for 16 weeks, beginning May 7, 2026, and concluding around August 27, 2026. ### Compensation & Benefits
Competitive compensation commensurate with experience
Potential to earn equity based on performance
Medical, dental, and vision coverage for employees and dependents at a nominal cost
Paid maternity leave
FSA and Dependent Care account options
401(k) Eligibility after 6 months of full-time employment
Collaborative, mission-driven work environment
If you take pride in delivering results, embrace challenges, and proactively seek improvement, then this is the place for you. You'll join a smart, humble, and collaborative team dedicated to improving healthcare. Employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, genetics, veteran status, sexual orientation, gender identity or expression, or any other legally protected status.
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