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Data Scientist, Optimization - Pricing

Lyft
CompanyLyft
CategoryData & Analytics
LocationNew York
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted7 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft Ads is one of Lyft’s newest and fastest-growing businesses, focused on building the world’s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey—before, during, and after a ride—by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes. The Pricing team is a centerpiece of Lyft’s marketplace. The team owns the models and software systems that determine the final 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. Planned Pricing is a fast-growing team within Pricing, focused on setting the most efficient price targets to drive both short term and long term business outcomes. As a Data Scientist specializing in Algorithms on the Planned Pricing team, you will develop mathematical models for core pricing systems and address diverse problems across optimization, prediction, machine learning, and inference. You will collaborate with cross-functional teammates and stakeholders to enhance algorithms, build and scale our systems, and drive business growth. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions and decisioning frameworks. 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 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 Experience: 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 Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible Subsidized commuter benefits Monthly Lyft credits and complimentary Lyft Pink membership Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, nationa
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