Data Scientist: Production Modeling & Analytics | Remote

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

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.