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Data Scientist, Risk Solutions
Data Scientist, Risk Solutions
As a Data Scientist on the Risk Solutions team at Lyft, you will leverage data science to enhance community safety and platform financial resilience. This role involves identifying opportunities, building predictive models, designing experiments, and collaborating with cross-functional teams to reduce accident frequency and claim severity.
About the role
About the Role
Data Science is at the heart of Lyft’s products and decision-making. As a Data Scientist on the Risk Solutions team, you will drive a mission critical to both the safety of our community and the financial resilience of our platform. You’ll partner cross-functionally with Product, Engineering, Actuarial and Claims teams to transform complex data into actionable strategies. This role offers a direct path to high-impact innovation for problem-solvers eager to apply high-level data science to real-world safety and financial challenges.
Responsibilities
- Leverage large-scale data and analytic frameworks to identify high-impact opportunities to reduce the total cost of claims.
- Partner with product managers, engineers, actuaries, claims, and operators to translate data insights into decisions and action.
- Construct and fit statistical, machine learning, or optimization models.
- Design and analyze online experiments; communicate results and act on launch decisions.
- Develop analytical frameworks to monitor business and product performance.
- Establish metrics that measure the health of our products, the business, as well as the driver experience.
- Collaborate with the Claims team to identify high-impact opportunities where data-driven interventions can reduce the total cost of claims.
Experience
- Degree in a quantitative field such as statistics, actuarial science, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience.
- 5+ years of industry experience in a data science, analytics, or management consulting role.
- End-to-end experience with data, including querying, aggregation, analysis, and visualization.
- Ability to manage, influence, negotiate, and inspire others in a fast-moving environment.
- Proficiency in SQL and Python.
- Experience with insurance claims analytics a plus.
- Strong oral and written communication skills, and ability to collaborate with cross-functional partners.