Staff Data Scientist: LTV & Growth Analytics (Hybrid)

Midi Health; San Francisco (CA); Hybrid; USD 210,000 - 240,000; Full time

Benefits offered by this job

Equity

Comprehensive Benefits

Lunch in Office

Hybrid work in Palo Alto

Job summary

Midi Health in Palo Alto is seeking a Senior or Staff Data Scientist to own end-to-end data frameworks for Unit Economics, linking customer acquisition, multi-product lifecycles, reimbursement cycles, and cost structures.

You will bridge Data Science with Finance, Marketing and Operations, building LTV, attribution, and pricing models, while driving strategic decisions on spend, product pricing, retention and long-term profitability.

Qualifications

• Advanced modeling and causal inference techniques.
• Production-grade ML development and deployment.
• Rigorous evaluation, backtesting, and drift detection.
• Attribution models and LTV analysis.
• Python for statistics and SQL for data manipulation.
• Simulation design and stochastic modeling.

Responsibilities

• Bridge Estimated vs. Realized LTV with healthcare reimbursements.
• Predict reimbursement rates across insurance allowables and self-pay tracks.
• Incorporate margins including licensing costs and wages.
• Optimize cross-product attribution and portfolio margins.
• Design pricing experiments to maximize margins while preserving retention.
• Build attribution models and churn survival analyses.
• Develop Monte Carlo macro-simulations for stress-testing the business model.

Skills

Advanced Modeling

Production ML

Model Evaluation

Attribution & LTV

Python

SQL

Simulation Design

LLMs & AI

Causal Inference

Marketing Analytics

Education

Master’s in Economics

PhD in Econometrics

Quantitative Discipline

Tools

Python

SQL

Monte Carlo

LLMs

Job description

Midi Health in Palo Alto is seeking a Senior or Staff Data Scientist to own end-to-end data frameworks for Unit Economics, linking customer acquisition, multi-product lifecycles, reimbursement cycles, and cost structures.

You will bridge Data Science with Finance, Marketing and Operations, building LTV, attribution, and pricing models, while driving strategic decisions on spend, product pricing, retention and long-term profitability.