Senior Data Scientist, Lyft
Algorithms, Lyft Biz
$136.2-170.2k
More information about location
3+ days a week in office
Ride sharing company
Be an early applicant
Ride sharing company
1001+ employees
Be an early applicant
$136.2-170.2k
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 bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of technical leadership in fast-paced, cross-functional environments
- Master’s or PhD in Machine Learning, Computer Science, Statistics, Optimization, or a related quantitative field (or equivalent applied experience)
- Industry Background: 5+ years of hands-on experience developing, deploying, and maintaining production machine learning models and optimization systems
- Core Technical Expertise: Deep knowledge of supervised/unsupervised learning, ranking/decisioning systems, probabilistic modeling, and causal inference
- Technical Stack: Strong proficiency in Python, modern ML frameworks (PyTorch, TensorFlow, scikit-learn), and distributed data systems (Spark, Snowflake, Databricks)
- Production ML Systems: Hands-on experience building end-to-end ML architectures, including online/batch pipelines, feature engineering, and automated monitoring frameworks
- Experimental Design: Demonstrated track record of designing rigorous experimentation strategies, A/B tests, and offline/online validation methodologies
- Domain Ownership: Proven ability to independently drive multi-project algorithmic scopes and navigate technical ambiguity from ideation to delivery.Communication & Leadership: Exceptional ability to translate complex technical concepts for non-technical stakeholders, alongside a history of mentoring peers and raising technical bars
What the job involves
- Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions
- We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products
- Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently
- Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools
- These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs
- We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite
- In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners
- You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation
- This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings
- Technical Leadership: Lead complex Machine Learning, AI, and causal inference initiatives across Lyft Business products (Business Travel, Lyft Pass, Concierge) in ambiguous, high-impact problem spaces
- End-to-End Modelling: Own the complete lifecycle of algorithmic solutions—from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration
- Production Deployment: Partner closely with Engineering to build and scale production-grade ML systems, real-time inference services, batch pipelines, and feature stores
- Experimentation & Rigor: Define offline/online metrics, evaluation frameworks, and A/B testing strategies to ensure algorithms are reliable, fair, and aligned with business outcomes
- System Optimization: Continually improve model performance across latency, accuracy, cost, and reliability using advanced tuning and scientific rigor
- Algorithmic Innovation: Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph-based methods to unlock new product capabilities
- Cross-Functional Influence: Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams
- Mentorship & Quality Bar: Mentor junior and mid-level scientists, providing technical guidance, conducting modeling critiques, and contributing to Lyft's broader ML standards and tooling
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 trialled 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, whilst the acquisition of European competitor Freenow could add 6 million new riders to its platform in 2026.
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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