Lead Data Scientist
Lead Data Scientist owning development of core predictive AI/ML models on messy healthcare claims and clinical data to identify waste and improve behavioral health outcomes for payers. Requires 8+ years experience, leadership of data science teams, production model deployment, and strong Python/SQL/ML skills.
About the job
Responsibilities
- Design and deploy predictive, risk-scoring, and optimization models that identify waste, inappropriate utilization, and care improvement opportunities across behavioral health services.
- Help define and evolve our data science stack, from feature stores and pipelines to model monitoring and evaluation frameworks.
- Dive deep into claims and clinical data to uncover trends, outliers, and actionable insights.
- Partner with client teams to translate complex models into clear insights that demonstrate ROI, inform payer workflows, and maintain clear, impactful dashboards.
- Collaborate with the CEO, CPO, and engineering team to guide product direction, data strategy, and key client engagements.
Requirements
- 8+ years of experience in data science or advanced analytics (preferably in healthcare or health plans; experience with claims and clinical data strongly preferred).
- Deep expertise in statistical modeling, causal inference, and ML (Python, SQL, and related libraries such as scikit-learn, statsmodels, PyTorch, or similar).
- Familiarity with healthcare data standards (claims, eligibility, EHR/clinical data, coding sets like ICD, CPT, HCPCS).
- Experience building production-grade models and deploying them in analytical or product environments.
- Proven experience building, mentoring, and leading high-performing data science or analytics teams.
- Scrappy with an entrepreneurial mindset: resourceful, proactive, thrives in ambiguity, and moves fast.
- Excellent communication skills and ability to translate complex data into clear business insights.
Nice-to-Haves
- Experience with claims and clinical data.
- Background in healthcare or health plans.
Compensation and Benefits
- Flexible hybrid arrangement: ~3 days/week at San Francisco office (Financial District).
- Unlimited vacation policy.
- Paid parental leave.
- Medical, dental, and vision insurance.
- Pre-tax commuter benefits.
- 401(k).
- Significant equity as an early employee.
- Direct mentorship from experienced founders.
- Ground-floor opportunity to help build a team and culture.
- Regular team events and off-sites.
- Company-provided equipment and home office setup.
Skills
Python, SQL, scikit-learn, Statsmodels, PyTorch, Causal Inference, Statistical Modeling, Machine Learning, Claims Data, Clinical Data, Icd, Cpt, Hcpcs
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