Home › Companies › Lyft › Applied Scientist- Pricing, Dynamic Pricing & Offer Selection
Applied Scientist- Pricing, Dynamic Pricing & Offer Selection
Lyft · New York, NY · Hybrid · Active · $140,800–$176,000 / year · Greenhouse
Job facts
| Field | Value |
|---|---|
| Company | Lyft |
| Title | Applied Scientist- Pricing, Dynamic Pricing & Offer Selection |
| Normalized title | - |
| Department / team | Pricing |
| Location | New York, NY, United States |
| Work model | Hybrid / Hybrid |
| Employment type | - |
| Salary | $140,800–$176,000 / year |
| Status | active |
| ATS provider | Greenhouse |
| Posted / first seen | 2026-02-11 / 2026-05-29 |
| Changed / last seen | 2026-06-04 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Lyft. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Greenhouse. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in Pricing. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Lyft |
| Source | 5fc2601d-43e7-4c04-81d6-28aa2a8c9d05 |
| ATS provider | Greenhouse |
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.
The 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.
As 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.
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, systems and decision frameworks.
Responsibilities
Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
Write 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.
Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.
Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems
Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes
Drive collaboration and coordination with cross-functional teams
Experience
M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields
2+ years of algorithms experience in a technology company setting
Proficiency with Python and working in a production coding environment
Passion for solving unstructured and non-standard mathematical problems and building impactful machine learning models leveraging expertise in one or multiple fields.
Strong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models
Strong verbal and written communication skills with a good track record of collaborating 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, 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. 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
The 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. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Full job record
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| Board ID | 5fc2601d-43e7-4c04-81d6-28aa2a8c9d05 |
| Provider | greenhouse |
| Provider Job Key | 8403370002 |
| Title | Applied Scientist- Pricing, Dynamic Pricing & Offer Selection |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York, NY |
| Department | Pricing |
| Team | — |
| Employment Type | — |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | 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 Min | 140,800 |
| Salary Max | 176,000 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://app.careerpuck.com/job-board/lyft/job/8403370002?gh_jid=8403370002 |
| Apply URL | https://app.careerpuck.com/job-board/lyft/job/8403370002?gh_jid=8403370002 |
| First Seen At | 2026-05-29 22:58:54Z |
| Last Seen At | 2026-06-06 20:29:23Z |
| Last Checked At | 2026-06-06 20:29:23Z |
| Last Changed At | 2026-06-04 11:13:38Z |
| Inactive At | — |
| Source Posted At | 2026-02-11 19:44:32Z |
| Source Updated At | 2026-06-04 09:10:14Z |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=lyft/date=2026-06-06/2026-06-06T20-29-23-450Z-504c4a22ad24d76f0237316a7e4ab4918cafef3b5579b1ea51792a133c50aa43.json |
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