Data Scientist, Lyft
Algorithms, Lyft Business
CA$108-135k
Ride sharing company
Job no longer available
Ride sharing company
1001+ employees
Job no longer available
CA$108-135k
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, experimentation; strong business acumen in B2B contexts; and a proven track record of leading teams in fast-paced, cross-functional environments
- Master’s degree or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field; or equivalent practical industry experience
- 3 years of applied experience building, evaluating, and deploying ML models or algorithms in production systems
- Strong proficiency in Python, applied ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn), and familiarity with ML Ops concepts (feature stores, model deployment, monitoring)
- Experience working with large-scale datasets and distributed data processing tools and vendors (e.g., Spark, Snowflake, Databricks)
- Hands-on experience with algorithm development, supervised/unsupervised learning, time-series, optimization, or ranking/recommendation systems
- Demonstrated ability to write clean, reliable, production-ready code and collaborate with Engineering on integrations, APIs, and model serving
- Experience with A/B testing, experiment setup, or causal inference fundamentals
- Ability to break down ambiguous problems, conduct rigorous analyses, and deliver actionable technical solutions
- Strong communication skills, with the ability to explain complex modeling concepts to technical and non-technical stakeholders
- A track record of impactful technical execution, intellectual curiosity, strong ownership, and a bias for action
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 Data Scientist to lead initiatives across the entire Lyft Business product suite
- In this role, you will shape the vision, define the roadmap, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our partners
- You’ll collaborate closely with Product, Engineering, Design and Go-to-Market teams to build 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
- Design, develop, and deploy production-grade algorithms and machine learning models that power Lyft Business products such as Business Travel, Lyft Pass, and Concierge
- Own the end-to-end lifecycle of modeling solutions—from problem definition, data exploration, feature engineering, and model development to validation, deployment, and post-launch monitoring
- Translate ambiguous business problems into measurable, technical solutions, collaborating closely with Product, Engineering, and cross-functional stakeholders
- Implement scalable model pipelines and contribute to high-quality, maintainable code used in production services
- Conduct deep exploratory and causal analyses on large-scale datasets to identify opportunities for growth, operational efficiency, fraud detection, dispatch quality, pricing optimization, and user experience improvements
- Run experiments and support causal inference frameworks, ensuring algorithm changes are rigorously measured and validated
- Benchmark, tune, and optimize models for performance at scale—latency, throughput, reliability, and fairness
- Contribute to technical documentation, model cards, reproducibility pipelines, and internal best practices
- Stay current with emerging ML/AI research and proactively identify opportunities to introduce new techniques that enhance product capabilities
- Collaborate in cross-functional planning, influencing direction through strong technical reasoning and data-driven insights
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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