About this role
The Marketplace team at Lyft builds dynamic pricing systems that leverage real-time and historical data to set prices for every single ride while balancing prices and estimated times of arrival. Members of this group focus on solving open-ended problems in pricing theory to accelerate business growth and deliver on financial metrics.
Daily work centers on collaborating with Product and Engineering to prototype, build, and scale end-to-end dynamic pricing models. Professionals who thrive here are data-driven, eager to learn quickly, and comfortable shaping both current and future roadmaps through applied domain knowledge.
What you will do
- Partner with other scientists, pricing colleagues, and external teams to formalize business and mathematical problems.
- Perform complex data analysis to uncover root causes and deepen understanding of core challenges.
- Develop and fit statistical, machine learning, or optimization models.
- Write production code and collaborate with software engineers to ship models.
- Design, implement, and analyze both simulated and live experiments to facilitate launch decisions.
- Communicate findings effectively to product, engineering, and executive leadership.
What you need
- Hold a Master of Science or Ph.D. in Computer Science, Economics, Statistics, Mathematics, or a related quantitative field.
- Bring 1 to 4 years of professional experience for Ph.D. holders, or 3 to 5 years for Master's degree holders in a data science role.
- Demonstrate proficiency with Python or another interpreted language such as R or Matlab.
- Possess the ability to write structured and efficient SQL queries across multiple large data sets.
- Have end-to-end data handling capabilities, spanning querying, aggregation, analysis, and visualization.
- Demonstrate strong oral and written communication skills alongside cross-functional collaboration abilities.
Nice to have
- Experience in causal inference
- LTV modeling experience
- Econometrics background
- User choice modeling experience
Benefits
- Great medical, dental, and vision insurance options with additional programs available when enrolled
- Mental health benefits, family building benefits, and child care and pet benefits
- 401(k) plan with company match
- Discretionary paid time off for salaried team members alongside 12 observed holidays
- 18 weeks of paid parental leave for biological, adoptive, and foster parents
- Subsidized commuter benefits, monthly Lyft credits, and complimentary Lyft Pink membership
Skills and tech stack
Questions candidates ask
What is the remote or hybrid work policy?
Team members are expected to work in the office three days per week on Mondays, Wednesdays, and Thursdays. Additionally, hybrid roles offer the flexibility to work from anywhere for up to four weeks per year.
What is the salary range for this role?
The expected base pay range for this position in the San Francisco area is $128,000 to $160,000. This is not inclusive of potential equity offerings, bonuses, or benefits, and depends on factors such as qualifications and experience.
What programming languages and tools are used?
The work involves proficiency in Python or another interpreted language like R or Matlab. Practitioners must also be skilled in SQL to write structured and efficient queries involving multiple large data sets.
What kind of background is required?
Candidates need an M.S. or Ph.D. in Computer Science, Economics, Statistics, Mathematics, or another quantitative field. Professional experience requirements range from 1 to 4+ years for Ph.D. holders or 3 to 5 years for Master's degree holders in a data science capacity.