{"id":2935924,"url":"https://alion.io/job/lyft-applied-scientist-pricing-dynamic-pricing-offer-selection","title":"Applied Scientist- Pricing, Dynamic Pricing & Offer Selection","company":{"id":234,"name":"Lyft","domain":"lyft.com","url":"https://alion.io/company/lyft","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":91,"open_postings":17,"ghost_share":0,"stale_share":0.353,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":140800,"max":176000,"currency":"USD","period":"year","gross":null,"usd_annual":176000},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-02-11T19:44:31Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T12:40:35Z","board_verified":true,"closed_at":null,"days_open":252,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":252},"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.\nThe Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention.\nAs an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. \nWe 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, systems and decision frameworks.\nResponsibilities\nPartner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context\nWrite production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries.\nPerform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. \nEvaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems\nEstablish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes\nDrive collaboration and coordination with cross-functional teams\nExperience\nM.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields\n2+ years of algorithms experience in a technology company setting\nProficiency with Python and working in a production coding environment\nPassion for solving unstructured and non-standard mathematical problems and building impactful machine learning models leveraging expertise in one or multiple fields.\nStrong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models\nStrong verbal and written communication skills with a good track record of collaborating with others to solve a problem\nBenefits: \nGreat medical, dental, and vision insurance options with additional programs available when enrolled\nMental health benefits\nFamily building benefits\nChild care and pet benefits\n401(k) plan with company match to help save for your future\nIn addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off\n18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible\nSubsidized commuter benefits\nMonthly Lyft credits and complimentary Lyft Pink membership\nLyft 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, 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.\nLyft 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. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid\nThe expected base pay range for this position in the San Francisco area is $140,800 - $176,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. 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