Senior Data Scientist, Algorithms, Forecasting and Realtime Optimization Platform

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

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.

The Forecasting and Real-Time Optimization Platform (FORTOP) team in Lyft's Rideshare Experience & Marketplace (REM) org provides reliable, real-time market supply and demand signals and forecasts that power the systems making critical automated decisions for Lyft's business. These signals feed many of Lyft's most important marketplace products, including Dynamic Pricing, Real-Time Supply Management, Fulfillment, etc. As a Senior Data Scientist on FORTOP, you will improve marketplace efficiency by designing, training, and applying machine learning models that deliver accurate real-time and forecast signals under dynamic conditions. We're looking for a driven Senior Data Scientist who is passionate about solving challenging problems with machine learning, and who is excited to work in a fast-paced, innovative, and cross-functional environment where they will take on some of the most interesting and impactful modeling problems in ridesharing.

Responsibilities:

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\

Experience:

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

Benefits:

Great medical, dental, and vision insurance options with additional programs available when enrolled

Mental health benefits

Family building benefits

Child care and pet benefits

401(k) plan with company match to help save for your future

In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off

18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Subsidized commuter benefits

Monthly Lyft credits and complimentary Lyft Pink membership

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Seattle area is $136,160 - $170,200, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.