Develop mathematical optimization and ML models for Lyft's Planned Pricing systems to set efficient price targets. Requires PhD in quantitative field, strong optimization experience, and Python proficiency in production environments.
128k – 160k
HybridData Science
About the role
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
Be 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
Requirements
Ph.D. in Operations Research, or other quantitative fields or related work experience
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 verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem
Nice-to-Haves
Experience in pricing, marketplace, or transportation domains
Compensation and Benefits
Expected base pay range for New York City: $128,000 - $160,000 (not inclusive of equity, bonus, or benefits)
Great medical, dental, and vision insurance options
Mental health benefits, family building benefits, child care and pet benefits
401(k) plan with company match
Discretionary paid time off (salaried), 15 days PTO (hourly), 12 observed holidays
18 weeks of paid parental leave
Subsidized commuter benefits
Monthly Lyft credits and complimentary Lyft Pink membership
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