Data Scientist, Algorithms - Pricing

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 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 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 Senior 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.

Responsibilities:

• 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

Experience:

• Ph.D. in Operations Research, Statistics, Economics, or other quantitative fields or related work experience. 
• 2+ years professional experience in a technology companies
• Proven experience with building and evaluating optimization and inference 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

Benefits:

• Great medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
• 401(k) plan to help save for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

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, Thursdays and a team-specific third day. 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 New York City area is $144,000 - $180,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.