About Jaan Health: Chronic Health Management Platform for US

<h2><strong>Lead Data Scientist, Causal Inference &amp; Clinical Outcomes Contractor</strong></h2> <p><strong>Location:</strong> Remote</p> <p><strong>Job Type:</strong> Contract to Hire or Full-Time (Flexible) </p> <p><strong>Job Reports To:</strong> Director of Business Intelligence</p> <p><strong>Compensation</strong></p> <p>Contract: $100–$160 per hour, depending on experience.<br>Direct Hire: Competitive base salary, flexible and commensurate with experience.</p> <p>Compensation will be determined based on the candidate's qualifications, experience, and overall fit for the positio</p> <h3><strong>About Jaan Health/Phamily</strong></h3> <p>Jaan Health is a leading AI-based care management company serving healthcare providers. For nearly a decade, the company has leveraged its easy-to-use, proprietary technology to enable health systems, medical groups, and ACOs to deliver high-quality, high-ROI proactive care to hundreds of thousands of previously underserved patients.</p> <p>Phamily, the company's core technology platform, has transformed chronic disease management with clinically tested AI and easy-to-use technology that enables physicians and care teams to offer high-touch, individualized patient care that has been proven to reduce investment in extra labor and the overall cost of care. Phamily helps ensure healthcare providers are compensated fairly for providing high-quality care between office visits, while improving the lives of patients with chronic diseases. Learn more at phamily.com.</p> <h3><strong>Job/Role Description</strong></h3> <p>We are seeking an analytical powerhouse to redefine proactive healthcare as our <strong>Lead Data Scientist for Causal Inference &amp; Clinical Outcomes</strong>. In this 16-week engagement starting <strong>May 7, 2026</strong>, 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.</p> <p>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.</p> <h3><strong>Key Responsibilities</strong></h3> <ul> <li><strong>Study Design &amp; Execution:</strong> Lead a longitudinal, quasi-experimental study starting May 7 to measure clinical outcomes, specifically hospitalization frequency and discharge follow-ups.</li> <li><strong>Causal Inference Modeling: </strong>Apply advanced methodologies (e.g., propensity score matching) to observational data to estimate counterfactual patient outcomes with minimal bias.</li> <li><strong>Actuarial-Grade Validation:</strong> Develop and refine statistical models that will be thoroughly vetted and approved by customer actuaries.</li> <li><strong>Stakeholder Management: </strong>Serve as the primary analytical face to SCMG, gathering requirements and aligning on clinical/business definitions of success.</li> <li><strong>Data Storytelling</strong>: Translate complex statistical findings into compelling presentations and client-ready reports for both technical and non-technical leadership.</li> <li><strong>Vendor Audit &amp; Wrap-up:</strong> Extract usable value from an existing outsourced study, close out the vendor contract, and integrate relevant findings into the final study.</li> <li><strong>Technical Infrastructure:</strong> Navigate and build analytics reporting infrastructure using SQL, Python, dbt, Redshift, and Looker.</li> <li><strong>Project Handoff: </strong>Ensure all code is clean and reproducible for final handover to the internal Phamily BI team.</li> </ul> <h3><strong>Requirements</strong></h3> <ul> <li><strong>Health-Tech Expertise:</strong> Deep experience in causal inference, metric design, and clinical outcomes evaluation.</li> <li><strong>Data Proficiency:</strong> Extensive experience working with complex EHR and healthcare claims data.</li> <li><strong>Advanced Analytics Toolkit:</strong> Highly capable in Python, R, SQL, dbt, Redshift, and Looker.</li> <li><strong>Statistical Matching:</strong> Proven experience developing algorithms for high-dimensional statistical matching with large datasets.</li> <li><strong>Security Standards:</strong> Practical experience maintaining strict PHI security protocols while building data infrastructure.