Applied Scientist- Pricing, Dynamic Pricing & Offer Selection

About the Role

Lyft’s Dynamic Pricing & Offer Selection team determines optimal prices and ETAs in real time, balancing supply and demand in its two-sided marketplace to improve conversion and retention.

As an Applied Scientist specializing in Machine Learning and Operations Research, you will develop mathematical models and launch algorithms that power pricing and ETA decisions. You will build ML and optimization models and production pipelines that scale to millions of calls per day, collaborating with Product Managers, Engineers, Analysts, and other Pricing stakeholders.

Responsibilities

• Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within their business context.
• Write production-quality code and design, build, and deploy production-grade ML and optimization models, including custom methods and tooling beyond off-the-shelf libraries.
• Analyze data and build proof-of-concepts to propose solutions to new and existing problems.
• Evaluate machine learning systems against business goals and collaborate with Engineers to implement robust algorithms in live systems.
• Establish metrics and measurement methodologies to monitor product health and impacts on users and marketplace outcomes.
• Drive collaboration and coordination across cross-functional teams.

Qualifications

• M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science, or other quantitative fields.
• At least 2 years of algorithms experience in a technology company setting.
• Proficiency with Python and experience working in a production coding environment.
• Passion for solving unstructured, non-standard mathematical problems and building impactful machine learning models.
• Strong understanding of machine learning methodologies and proven experience building and evaluating optimization or machine learning models.
• Strong verbal and written communication skills and a track record of collaborating to solve problems.
• Ability to balance complexity and efficiency when translating business problems into reliable solutions, systems, and decision frameworks.

Work Arrangement

• Hybrid role in San Francisco, with office attendance required on Mondays, Wednesdays, and Thursdays.
• Working in the office at least 3 days per week is an essential function of the role.
• Flexibility to work from anywhere for up to 4 weeks per year.

Compensation

• Expected annual base pay in San Francisco: $140,800–$176,000, excluding potential equity, bonus, and benefits.
• Compensation depends on qualifications, experience, geographic location, and other factors. The recruiter can provide location-specific details.

Benefits

• Medical, dental, and vision insurance, with additional programs available upon enrollment.
• Mental health, family building, child care, and pet benefits.
• 401(k) with company match.
• 12 observed holidays; discretionary paid time off for salaried employees and 15 days of paid time off for hourly employees.
• 18 weeks of paid parental leave for biological, adoptive, and foster parents.
• Subsidized commuter benefits.
• Monthly Lyft credits and complimentary Lyft Pink membership.