Data Scientist, Algorithms, Optimization - Fulfillment

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 central to Lyft's products and decision-making. As a Data Scientist on the cross-functional team, you will work in a dynamic environment, tackling a variety of problems from shaping critical business decisions to building algorithms that power our products. We seek passionate, driven Data Scientists to address some of the most interesting and impactful problems in ridesharing.

As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Fulfillment team, you will collaborate with cross-functional teammates and stakeholders to enhance algorithms for matching rideshare supply and demand in real time and develop product offerings to improve the experiences of Lyft Riders and Drivers.

Responsibilities:

• Leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products
• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Construct and fit statistical, machine learning, or optimization models
• Write production modeling code; collaborate with Software Engineers to implement algorithms in production
• Design and implement both simulated and live traffic experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions
• Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
• Drive collaboration and coordination with cross-functional teams

Experience:

• M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
• 2+ years professional experience in a technology company setting
• Proven experience with building and evaluating machine learning models
• Proficiency with Python and working in a production coding environment
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Strong oral a