Senior Data Scientist, Lyft
Machine Learning, Rider Recommendations
$144-180k
More information about location
3 days a week in office
Ride sharing company
Job no longer available
Ride sharing company
1001+ employees
Job no longer available
$144-180k
More information about location
3 days a week in office
1001+ employees
Company mission
To improve people’s lives with the world’s best transportation.
Role
Who you are
- 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
What the job involves
- 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
- 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
Our take
Lyft has aimed for consistent growth, making sure to pitch itself as a more reliable and friendly ride-sharing option than its main competitor, Uber. Uber has a greater market share and operates globally, but Lyft hopes to compete by its focus on ride-sharing over Uber's more diversified business approach and as a more rider-friendly and greener alternative to Uber.
Operating only in the USA and Canada, Lyft is in a position of being less affected by global events than Uber but also more vulnerable to local conditions. As an example, while it doesn't face the regulatory hurdles around employment rights that Uber does, it is unable to balance out the cost of the unusually expensive US auto insurance across its operations.
In 2022, Lyft acquired PBSC Urban Solutions, a bike-share equipment and technology supplier, allowing Lyft to compete in new verticals and reaffirming its commitment to green transportation. It has also trialed and launched Lyft Assisted, where drivers help passengers from their door into the car to get to medical appointments. These developments chime well with Lyft's unique selling point as a friendlier and more environmentally aware ride-sharing app.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 14 rounds)
Jun 2018
$600m
LATE VC
Mar 2018
$200m
LATE VC
Total funding: $4.9bn
Company benefits
- Great medical, dental, and vision insurance options
- Mental health 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
- Family building benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
Company HQ
China Basin, San Francisco, CA
Articles
Leadership
John Zimmer
(Co-Founder)Originally an Analyst at Lehman Brothers, Zimmer then founded Zimride which was a private ridesharing company that pivoted into Lyft.
Logan Green
(Co-Founder)Founded Zimride, a private ridesharing company which later pivoted into Lyft.
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