Backed by GV.
About the role
We are looking for a highly strategic Senior or Staff Data Scientist to design, build, and own the end-to-end data framework that defines our business health: Unit Economics.
What they're looking for
- Advanced Modeling & Stats: Mastery of predictive modeling and Causal Inference techniques (e.g., uplift modeling, propensity score matching, synthetic controls, or diff-in-diff)
- Attribution & LTV: Proven track record building attribution models (algorithmic or heuristic) and handling survival analysis for churn and retention forecasting
- Programming & Querying: Advanced proficiency in Python for complex statistical analysis, alongside expert-level SQL for manipulating large data streams
- Simulation Design: Experience structuring systemic business simulations or stochastic modeling
- Modern AI Workflow: Active adoption and mastery of Large Language Models (LLMs) and generative AI tools within your personal development workflow to accelerate coding, debugging, documentation, and prototyping
- 8+ years of experience delivering high-impact data science solutions
More about this role
📍 Hybrid, Palo Alto (Hybrid – 2 days/week in office)
Job Type: Full-time, W2
We are looking for a highly strategic Senior or Staff Data Scientist to design, build, and own the end-to-end data framework that defines our business health: Unit Economics.
In this role, you won't just build standalone models; you will connect the dots between customer acquisition, multi-product lifecycles, complex healthcare reimbursement cycles, and operational cost structures. Your work will serve as the financial and analytical source of truth, directly influencing how we allocate marketing spend, price our products, manage retention, and project long-term profitability.
You will sit at the intersection of Data Science, Finance, Marketing, and Operations, acting as a critical strategic partner to executive leadership.
- Bridge Estimated vs. Realized LTV: Develop sophisticated lifetime value models that account for the volatility of healthcare reimbursements and the time value of money.
- Predictive Reimbursement Rates: Build models to predict actual reimbursement rates across a complex mix of insurance allowables and self-pay tracks, closing the gap between theoretical revenue and cash-in-hand.
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