Data Science Manager, Lyft
Real-Time Supply Management
CA$136-170k
More information about location
3+ days a week in office
Ride sharing company
Posted today
Ride sharing company
1001+ employees
Posted today
CA$136-170k
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
- The ideal candidate will have strong experience in algorithm development (particularly in optimization, machine learning, or causal inference), thrive in a fast-paced environment, and possess a hands-on, entrepreneurial mindset to drive results
- Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience
- 5+ years of hands-on technical experience in machine learning, causal inference, optimization, or data science, preferably with applications in real-time systems or marketplace dynamics
- 1+ years of management experience building, leading, and mentoring data science teams
- Proven track record of leveraging data science, optimization, and/or machine learning to drive significant business outcomes
- Experience guiding teams through ambiguous and complex technical challenges to deliver impactful solutions
- Strong understanding of experimental design and causal inference
- Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences
- Hands-on experience with large-scale data processing (e.g., Spark, SQL) and machine learning frameworks is highly desirable
- Familiarity with real-time bidding, dynamic pricing, or supply chain optimization is a strong plus
What the job involves
- We are looking for a Data Science Manager to lead data science initiatives for the Real-Time Supply Management (RTSM) team.
- You will play a pivotal role in developing the vision, setting roadmaps, and leading the execution of data science projects that directly impact Lyft's marketplace efficiency and driver engagement.
- You'll partner closely with product, engineering, and operations leaders to build and scale our real-time incentive systems, shape long-term strategy, and deliver on critical business goals.
- You will initially be hands-on in building models and pipelines, gradually shifting to more managerial responsibilities as the team grows.
- Lead, mentor, and grow a high-performing team of data scientists with diverse backgrounds, including optimization, experimentation, machine learning and causal inference
- Develop and deploy machine learning models, algorithms, and systems to optimize real-time supply management, including Bonus Zone budget allocation and Priority Mode effectiveness
- Define and drive the data science vision, strategy, and roadmap for RTSM, aligning with overall business objectives to improve market throughput and driver experience
- Provide strong technical guidance and coaching to the team on complex data science problems related to real-time decision-making and resource allocation
- Champion data-driven decision-making and prioritization within the RTSM team and with cross-functional partners
- Lead deep-dive analyses into large-scale datasets to identify opportunities for improving incentive efficiency, spend accuracy, and overall market health
- Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for real-time incentives
- Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies
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
-2% employee growth in 12 months
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
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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