Data Scientist - Production Modeling & Analytics

At Lyft, our purpose is to serve and connect by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft’s Data Science team develops mathematical and algorithmic systems that power the core services of the platform. In this role, you will work closely with Engineers, Product Managers, and Business Partners to frame complex real-world problems mathematically and operationally. You will build, fit, and deploy statistical, machine learning, and optimization models, turning non-standard data into actionable algorithmic decisions in production.

Key Responsibilities

• Problem Framing: Partner with Engineers, Product Managers, and Business Partners to define and frame complex problems mathematically within business contexts.
• Exploratory Data Analysis: Conduct end-to-end data processing—including querying, aggregation, deep-dive analysis, and visualization—to gain underlying system insights.
• Model Development: Construct, tune, and fit statistical, machine learning, and optimization models tailored to non-standard, unstructured problems.
• Production Implementation: Write clean, production-ready modeling code and collaborate with Software Engineers to integrate algorithms into live systems.
• Experimentation & Analytics: Design, execute, and analyze live traffic and simulated A/B experiments to evaluate model performance and guide launch decisions.
• Communication & Impact: Present technical findings and data-driven recommendations clearly to stakeholders and cross-functional leadership.

Requirements

Experience & Education

• Master’s degree (or foreign equivalent) in Mathematics, Statistics, Economics, Operations Research, or a related quantitative field.
• 2+ years of professional experience in a Data Scientist, Operations Research, or related quantitative role.

Technical Capabilities

• Demonstrated experience solving non-standard and unstructured mathematical or statistical problems.
• Hands-on expertise across the complete data lifecycle: querying, aggregation, exploratory data analysis, and data visualization.
• Strong proficiency coding in Python, alongside familiarity with other programming languages such as R or MATLAB.
• Track record of writing production-level code and collaborating with software engineering teams.
• Practical knowledge of experimental design, statistical testing, and live/simulated experiment evaluation.

Benefits & Workplace Perks

• Healthcare Coverage: Comprehensive medical, dental, and vision insurance options.
• Mental & Family Health: Mental health support, family building assistance, childcare, and pet care benefits.
• Retirement & Financial: 401(k) retirement plan with company matching options and pre-tax commuter benefits.
• Time Off: 12 observed holidays, discretionary paid time off for salaried team members, and up to 4 weeks of flexible remote work per year.
• Parental Support: 18 weeks of paid parental leave for biological, adoptive, and foster parents.
• Lyft Perks: Subsidized commuter benefits, complimentary Lyft Pink membership, and exclusive access to test new ridership features.
• In-Office Culture: Collaborative hybrid workspace model with team perks on in-office days (Mondays, Wednesdays, and Thursdays).