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# Senior Data Scientist, Marketplace

- **Company:** Lyft Inc
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $136,160.0 - $170,200.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Python (Programming Language), Machine Learning, Feature Engineering, Model Validation, Technical Debt, Scikit Learn, Information Technology, Marketplace
- **Published:** July 7, 2026
- **Apply:** https://dejobs.org/x/x/41A40903D7DF4D348F3A183917316B95/job/

## About the Role

* M.S. or Ph.D. in Statistics, Mathematics, Economics, Operations Research, Computer Science, or other quantitative fields or related work experience
 * 5+ years professional experience in a technology company setting involving a product
 * Proven experience with building and evaluating time series forecasting and machine learning models, ideally in real-time or large-scale production settings
 * Strong grasp of core ML fundamentals - feature engineering, model evaluation, and managing the bias-variance tradeoff
 * Proficiency with Python and modern ML libraries, and experience working in a production coding environment
 * End-to-end experience with data, including querying, aggregation, analysis, and visualization
 * Passion for solving unstructured and non-standard mathematical problems
 * Strong written and verbal communication; ability to align stakeholders and influence outcomes through reasoning and data

## Description

Data Science is at the heart of Lyft's products and decision-making. As a member of the Science team, you will work in a dynamic environment, where we embrace moving quickly to build the world's best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building the machine learning models and algorithms that power our internal and external products., * Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context, and shape roadmaps across cross-functional teams

 * Perform exploratory data analysis to gain a deeper understanding of the problem and the marketplace
 * Develop, fit, and evaluate time series forecasting and machine learning models
 * Write production model code; collaborate with Software Engineers to implement and scale models and algorithms in production, with attention to correctness, efficiency, consistency, and technical debt
 * Design and implement both simulated backtesting and live experiments; analyze experimental and observational data, communicate findings, and facilitate launch decisions
 * Define and uplevel monitoring of model and signal health; build and scale tooling that improves the efficiency of operational tasks


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