Data Scientist, Algorithms Pricing (Optimization)

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. Data Science is at the heart of 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 New Grad 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 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 (Optimization), or similar 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 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 Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in office to foster a collaborative work environment and company culture. 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, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. The expected base pay range for this position in the San Francisco Bay area is $128,000 – $160,000. 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. #J-18808-Ljbffr