At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.
Data Science is at the heart of 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 by leveraging optimization and inference to shape critical business decisions. We seek passionate, driven Data Scientists to address some of the most interesting and impactful problems in ridesharing.
We are hiring a Data Scientist to join the Pricing team. The Pricing team owns the models and software systems that determine the prices shown to riders. Working with our business and analytics partners, the team owns tools to ensure Lyft offers competitive prices while making efficient financial trade-offs. We’re looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment. In this role, you will report to a Data Science Manager.

EXPERIENCE:

• Ph.D. in Operations Research, or other quantitative fields or related work experience.
• 2+ years professional experience in a technology companies
• Proven experience with building and evaluating optimization 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 and written communication skills, and ability to collaborate and communicate with others to solve a problem

• Partner with Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
• Prioritize and lead deep dives into our data to uncover new product and business opportunities
• Being familiar with production code; collaborate with Software Engineers to implement algorithms and models in production
• Design, implement, and analyse different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Drive collaboration and coordination with cross-functional teams
• Provide coaching and technical guidance for other teammates