Applied Scientist- Pricing, Dynamic Pricing & Offer Selection

Reposted 20 Days Ago
Be an Early Applicant
New York, NY, USA
In-Office
141K-176K Annually
Mid level
Transportation
The Role
Develop machine learning models and optimize pricing algorithms to enhance Lyft's market dynamics, collaborating with cross-functional teams on real-world business problems.
Summary Generated by Built In

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.

Skills Required

  • M.S. or Ph.D. in Machine Learning, Operations Research, Statistics or Computer Science
  • 2+ years of algorithms experience in a technology company setting
  • Proficiency with Python in a production coding environment
  • Strong understanding of machine learning methodologies
  • Strong verbal and written communication skills

Lyft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lyft and has not been reviewed or approved by Lyft.

  • Healthcare Strength Corporate materials describe comprehensive medical, dental, and vision coverage with added access to One Medical and mental-health support, indicating a solid core health offering. This breadth positions health benefits as a relative strength for full-time employees.
  • Parental & Family Support Company information highlights paid parental leave for new parents, with flexibility in how time can be taken. This signals strong family support within the corporate package.
  • Leave & Time Off Breadth U.S. salaried employees have unlimited paid time off alongside company holidays, and hourly roles receive structured PTO and sick time. These policies point to ample time-off availability compared with many roles.

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The Company
HQ: San Francisco, CA
22,282 Employees

What We Do

Lyft was founded in 2012 by Logan Green and John Zimmer to improve people’s lives with the world’s best transportation, and is available to approximately 95 percent of the United States population as well as select cities in Canada. Lyft is committed to effecting positive change for our cities by offsetting carbon emissions from all rides, and by promoting transportation equity through shared rides, bikeshare systems, electric scooters, and public transit partnerships.

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