Data Scientist, Algorithms - Rider Pricing

Posted 18 Hours Ago
San Francisco, CA
Mid level
Transportation
The Role
As a Data Scientist, you will develop analyses and mathematical models for rider pricing at Lyft, working on optimization and prediction challenges. You'll collaborate with various teams to use data insights to drive decisions, establish performance metrics, and enhance rider and driver experiences.
Summary Generated by Built In

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft work in dynamic environments, where we embrace moving quickly to build the world’s best transportation. We take on a variety of problems ranging from shaping long-term business strategy with data, making short-term critical decisions, and building algorithms/models that power our internal and external products. 

As a Data Scientist, you will be developing analyses, metrics, dashboards, and mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We are hiring motivated experts in each of these fields. 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.

We are looking for a Data Scientist to join the Rider 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. Additionally, the team owns the development and maintenance of real-time and planned rider incentives with a goal of driving efficient ride growth. The team uses a wide range of causal inference, optimization and reinforcement learning methodologies to achieve these goals.

You will report to a Data Science Manager.

Responsibilities:

  • Leverage data and analytic frameworks to identify opportunities for growth and efficiency 
  • Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action
  • Design and analyze online experiments; communicate results and act on launch decisions
  • Develop analytical frameworks to monitor business and product performance
  • Establish metrics that measure the health of our products, as well as rider and driver experience
  • Provide coaching and technical guidance for the team
  • Prioritize and lead deep dives into our data to uncover new product and business opportunities
  • Facilitate and foster data-driven and informed decision making and prioritization

Experience:

  • M.S. or Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields or related work experience
  • 3+ years professional experience
  • Passion for solving unstructured and non-standard, ambiguous mathematical problems by leveraging expertise in one or multiple fields.
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization
  • Proficiency with Python, or another interpreted programming language like R or Matlab
  • Strong communicator. Able to coordinate with several teams of data scientists to deliver on complex initiatives. 
  • Strong business sense and understanding of experimentation methodologies.
  • Proficiency in SQL - able to write structured and efficient queries on large data sets
  • Experience in online experimentation and statistical analysis
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners

Benefits:

  • Great medical, dental, and vision insurance options
  • Mental health benefits
  • Family building benefits
  • In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
  • 401(k) plan to help save for your future
  • 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
  • Pre-tax commuter benefits
  • Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. 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 or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

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, Thursdays and a team-specific third day. 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 $124,000 - $155,000. 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. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Top Skills

Matlab
Python
R
The Company
HQ: San Francisco, CA
22,282 Employees
On-site Workplace

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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