Greenhouse ·
full-timeData Scientist, Optimization - Real-time Supply Management
Lyft · Toronto, Canada
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. 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. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collaborate with Software Engineers to implement algorithms in production. Perform exploratory data analysis to gain a deeper understanding of the marketplace and its users. Communicate findings and facilitate launch decisions with technical and non-technical stakeholders. Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies. Experience: Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Applied Math, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience. Passion for solving unstructured and non-standard mathematical problems, with 2+ years of hands-on experience in optimization (preferred), causal inference, or machine learning. End-to-end experience with data, including querying, aggregation, analysis, and visualization. Proficiency with Python. Strong ability to collaborate and communicate with others in a team setting. Experience seeking out and adopting new methods and techniques. Experience designing, running, and analyzing A/B tests to validate hypotheses and inform decision-making. Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan with company match to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible. Subsidized commuter benefits and Lyft ride credits Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the of
| Role | Data Scientist, Optimization - Real-time Supply Management |
|---|---|
| Company | Lyft |
| Location | Toronto, Canada |
| Type | internship |
| Compensation | Not disclosed |
| Posted | 2026-09-28 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4More at Lyft
Other jobs at Lyft
- Procurement COE Manager · San Francisco, CA
- Analytics Lead, Decisions & Insights · New York, NY
- Senior Software Engineer, Foundational Infrastructure & Networking · Toronto, Canada
- Sr. Manager, Accounts Payable · San Francisco, CA
- Stagiaire En Ingénierie De La Qualité Terrain, Matériel (été 2027) · Longueuil, Canada
Internships at Lyft
- Hardware Field Quality Engineer Intern (summer 2027) · Longueuil, Canada
- Business Systems Engineer Intern, Finance Technology (summer 2027) · Toronto, Canada
- Industrialization Engineer Intern (summer 2027) · Longueuil, Canada
- UX Research Intern (summer 2027) · Toronto, Canada
- Applied Scientist Intern (summer 2027) · San Francisco, CA
Explore Related Placements
// similar opportunities
You might also like
Data Scientist, Decisions - Mapping
Lyft
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to...
Staff Data Scientist - Ads Measurement, Signals, Privacy
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the intern...
Analytics Lead, Central Market Management
Lyft
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to...
Data Analyst, Go-to-market Sales Insights
Lyft
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to...
Manager Of Data Engineering
Robinhood
Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger gene...
['5 days/week onsite', '3+ years manager experience']
Program Manager, AV Operational Excellence
Lyft
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to...