Senior Data Scientist, Machine Learning, Rider Recommendations

Posted 15 Hours Ago
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New York, NY
Senior level
Transportation
The Role
As a Senior Data Scientist on the Rider Recommendations team at Lyft, you will develop advanced machine learning models to enhance rider experience, optimize recommendations, and drive user satisfaction. Collaborating with cross-functional teams, you will work on problem framing, exploratory data analysis, and experimentation methodologies to improve the platform's core services.
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. As a member of the Rider team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products. We’re looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems in ridesharing.

As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Rider Recommendations team, you will collaborate with cross-functional teammates and stakeholders to develop advanced machine learning models to enhance rider experience. By analyzing user behavior and leveraging data-driven insights, the team builds personalized recommendation systems that help deliver more relevant, engaging content and products. The Rider Recommendations team aims to optimize recommendations, drive user satisfaction, and improve overall platform engagement.

You will report to a Data Science Manager in the Rider Science team.

Responsibilities:

  • Drive the Science roadmap of the team’s problem area, leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products
  • Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
  • Perform exploratory data analysis to gain a deeper understanding of the problem
  • Construct and fit statistical, machine learning, or optimization models
  • Write modeling code; collaborate with Software Engineers to implement algorithms in production
  • Design and implement both simulated and live traffic experiments
  • Analyze experimental and observational data; communicate findings; facilitate decisions
  • Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
  • Drive collaboration and coordination with cross-functional teams
  • Advise teams on best practices. Be a thought leader and go-to expert for stakeholders and dependency teams

Experience:

  • M.S. or Ph.D. in Machine Learning, Statistics, Computer Science, Mathematics, or other quantitative fields
  • 4+ years professional experience in a technology company setting
  • Proven experience with building and evaluating machine learning models
  • Proven experience in leading high visibility projects and influencing others in a cross-functional team environment
  • Proficiency with SQL, Python and working in a production coding environment
  • Passion for driving business impact with data 
  • End-to-end experience with data, including querying, aggregation, analysis, modeling and visualization
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional and cross-team partners
  • Strong business sense and understanding of experimentation methodologies
  • Experience in online experimentation and statistical analysis.

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 New York City area is $132,480 - $165,600. 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

Python
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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