Book a car rental on Turo, skip the rental counter. From EVs and trucks to luxury vehicles, find the right car for your trip. Free cancellation on most trips. Backed by Kleiner Perkins and GV.
About the role
You are a creative and rigorous data scientist who is energized by mathematically complex, ambiguity-rich problems. You thrive at the intersection of econometrics, machine learning, and optimization, and you’re comfortable translating unstructured questions into statistical frameworks and deployed solutions.
What they're looking for
- PhD in a quantitative field such as economics, statistics, machine learning, etc
- Experience with marketplace or platform problems
- Background in structural modeling, market design, dynamic programming, or advanced statistical methods (hierarchical models, time-series forecasting, survival analysis, Bayesian inference, synthetic control)
- Track record shipping pricing or optimization systems to production
- Experience with AWS stack or similar cloud infrastructure
- Familiarity with Airflow or ML orchestration tools
More about this role
Turo’s Dynamic Pricing team builds the pricing intelligence that powers recommendations for 200,000+ vehicles globally: a foundational economic engine influencing tens of millions of pricing decisions each day.
These models directly shape guest demand, host profitability, and the overall efficiency and balance of our two-sided marketplace.
We’re looking for a Staff Data Scientist who combines deep modeling expertise with strong product intuition and an economics mindset. In this role, you will own complex pricing challenges spanning demand modeling, supply–demand dynamics, causal inference, and optimization under uncertainty.
You’ll join a small, high-impact team working across the full lifecycle. From research, development and deployment, to experimentation and iteration.
Lead dynamic pricing model development end to end, from problem framing through deployment and iteration, using demand modeling, causal inference, and market simulation.
Develop new approaches to pacing, lead-time dynamics, seasonality, and price elasticity to improve pricing accuracy and marketplace efficiency.
Build frameworks to measure how pricing decisions affect marketplace health, host earnings, and guest...
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