Data Scientist - Production Modeling & Analytics

The Briefed; Seattle (WA); Hybrid; USD 130,000 - 180,000; Full time

Benefits offered by this job

Healthcare Coverage

Mental & Family Health

Retirement & Financial

Time Off

Parental Support

Lyft Perks

In‑Office Culture

Job summary

Lyft is seeking a data scientist to frame complex business problems, conduct end‑to‑end data analysis, and develop production‑level models. You will collaborate with engineers, product managers, and business partners to turn insights into actionable decisions.

The role requires building and evaluating ML and optimization models, plus designing live and simulated experiments to guide launch decisions. A hybrid workplace with in‑office days supports collaboration.

Qualifications

• 2+ years of professional experience in a Data Scientist, Operations Research, or related quantitative role.
• Experience framing and solving non‑standard problems in real-world contexts.
• Proficiency in Python and familiarity with R or MATLAB for modeling and analysis.

Responsibilities

• Problem Framing: Collaborate with Engineers, Product Managers, and Business Partners to define problems mathematically in business contexts.
• Exploratory Data Analysis: Perform end‑to‑end data processing, querying, aggregation, and visualization to extract insights.
• Model Development: Build, tune, and deploy statistical, ML, and optimization models for unstructured problems.
• Production Implementation: Write production‑level modeling code and work with software engineers to deploy algorithms.
• Experimentation & Analytics: Design and analyze live traffic and A/B experiments to assess model performance.
• Communication & Impact: Present findings and recommendations clearly to stakeholders and leadership.

Skills

Problem framing

Exploratory data analysis

Model development

Production-grade code

Experiment design

Communication of findings

Education

Master’s degree in quantitative field

Tools

Python

R

MATLAB

Job description

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.

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 workplace model with team perks on in‑office days (Mondays, Wednesdays, and Thursdays).