# Senior Data Scientist, Rider New Products

**Company:** [Lyft](https://hotfix.jobs/companies/lyft)
**Location:** San Francisco, CA
**Role:** Data Science
**Salary:** $148k – $185k/yr
**Experience:** 3+ years
**Skills:** Causal Inference, Python, SQL, Experiment Design, Counterfactual Analysis, Statistical Modeling, Causal Models, Data Pipelines, Applied Statistics, Machine Learning
**Posted:** 2026-01-26

> Measures incremental impact of new rider product features using advanced causal inference, designs production-grade measurement systems, and partners with Product/Engineering to drive innovation and business growth. Requires 3+ years experience, Master's/PhD, Python/SQL proficiency.

## Job Description

## Responsibilities

- Own complex, open-ended incrementality measurement problems. Translate ambiguous product launches into concrete causal frameworks and experimental designs.
- Lead high-impact Causal Inference initiatives. Drive innovation by introducing advanced measurement techniques to quantify the incremental impact of new rider features.
- Partner deeply with Product, Engineering, and Finance. Define the technical vision for how Lyft evaluates innovation, ensuring that we move beyond simple correlations to understand the long-term drivers of rider behavior and value.
- Design and build production-grade measurement systems. Develop and deploy robust causal models pipelines that balance high scientific rigor with the practical constraints.
- Establish robust evaluation frameworks. Ensure that the "engine of innovation" is steering the business toward sustainable, incremental growth.
- Build reusable science infrastructure. Create internal libraries and best practices for causal discovery and automated measurement.
- Mentor and guide junior/mid-level scientists. Serve as a technical advisor on experimental design, statistical modeling, and fostering a culture of scientific excellence.

## Requirements

- Advanced Quantitative Background: Master’s or PhD in Economics, Statistics, Applied Math, Computer Science or equivalent high-impact industry experience.
- **3+ Years of Applied Experience**: Proven track record in applied science or data science, with a focus on deploying causal models that drive measurable business outcomes.
- Deep product intuition and hands-on experience with causal methods.
- **Strong proficiency in Python and SQL**.
- Experienced in defining and executing sophisticated evaluation strategies, including advanced experiment design and counterfactual analysis to isolate incrementality.
- Proven ability to align cross-functional partners, influence technical architecture, and challenge scientific assumptions to guide high-level product strategy.
- Excellent ability to articulate complex causal concepts, trade-offs between rigor and speed, and scientific findings to both technical peers and executive stakeholders.

## Preferred Qualifications

- Demonstrated ability to own high-stakes, open-ended problem spaces, translating vague business questions into rigorous scientific roadmaps.
- Experience in mentoring other scientists, elevating the bar for technical quality, and establishing best practices for modeling and scientific reasoning.

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