About the Team:

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 Senior 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. 

What you will do:

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.

You think in equations as easily as in product narratives, and you can reason about incentives, elasticity, and market equilibrium without needing perfect data. You love working on consumer marketplaces, experimenting in production, and seeing your models influence real-world outcomes.

Responsibilities:

Modeling & Causal Inference

• Lead end-to-end development of dynamic pricing models. From problem framing to 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 conversion; design experiments that account for two-sided marketplace interactions and spillover effects.
   

Product & Cross-Functional Leadership

• Translate ambiguous business problems into deployable modeling solutions and influence product strategy through clear communication to both technical and executive audiences.
   

• Shape and evaluate product initiatives that improve host experience and profitability, aligning cross-functional teams on metrics, assumptions, and key trade-offs.
   

Technical Excellence

• Write production-ready Python code; own model deployment, monitoring, and retraining.
   

• Drive team standards for reproducibility, ML ops, and scientific rigor.

Your profile:

• 5+ years of relevant industry experience and an advanced degree in a quantitative field.

• Deep expertise in statistics, econometrics, optimization, and ML; with demonstrated application to pricing or prediction problems.

• Strong causal inference background: experiment design, quasi-experimental methods, and structural modeling.

• Experience with marketplace or platform problems and a solid understanding of economics, including supply–demand dynamics and elasticity modeling.

• Python proficiency; fluent in SQL and large-scale data work.

• Exceptional communication skills, capable of distilling complex modeling work into clear, strategic narratives for executive leadership.

• Self-driven learner with strong ownership, attention to detail, and a drive for delivering real business impact.

Preferred Qualifications:

• PhD in a quantitative field such as economics, statistics, machine learning, etc.

• Background in 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.

For this role, the target base salary range in San Francisco is $156,000-$195,000 annually. This role is also eligible for equity and benefits. In general, our ranges reflect the market-based target for new hire salaries based on the level and location of the role. Within the range, individual pay is determined by objective factors assessed during the application and interview process, such as job-related skills, experience, and relevant education or training. We encourage you to talk with your recruiter to learn more about the total compensation and benefits available for this role.

Turo highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Turists will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Turo considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Turo offers.

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