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.
Salary not listed
Hybrid8+ YOEData Science
About the role
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.
Lead and grow a team of 4-6 data scientists at a healthcare startup. Own predictive analytics, marketplace forecasting, and production ML models (matching, quality scoring) while partnering cross-functionally to drive business impact. Requires 6+ years DS experience including 2+ years managing technical teams, strong Python/ML/SQL skills, and production ML expertise.
Salary not listed
Remote6+ YOEData Science
Senior Data Science Manager, Growth & Retention Marketing
PrizePicksAtlanta, GA
Lead a team of data scientists focused on marketing analytics for retention and acquisition. Oversee production ML models, causal inference projects, and LLM integration to drive marketing decisions and business outcomes. Requires 7+ years data science experience including 3+ years managing teams.
180k – 210k
Remote7+ YOEData Science
Senior Manager, Data Science
HonorUnited States
Lead a Data Science team building production ML, optimization, and AI systems (including agentic workflows) to solve complex operational problems in caregiver-client matching, scheduling, and risk identification for home care. 7+ years experience with 3+ years managing teams; player-coach role partnering with Product, Engineering, and Operations.
229k – 254k
Remote7+ YOEData Science
Senior Data Scientist
PlaidSan Francisco, CA +2
Senior Data Scientist on Plaid's Network Value team supporting the Guard product. Translate product questions into analysis, build metrics/OKRs/dashboards, run experiments, and drive data-informed decisions for a 0-to-1 user-facing fintech product.
191k – 263k
Hybrid5+ YOEData Science
Applied Science / Data Science Leader
AttentiveSan Francisco, CA
Lead and grow a team of Applied Scientists and Data Scientists to define the data science vision, develop ML and experimentation solutions, and influence product strategy and business growth through deep analysis and cross-functional partnerships. Requires 8+ years in data science/ML, 3+ years managing teams, advanced degree, and expertise in causal inference and Python/SQL.