Data Science Intern, Lyft
Algorithms, Summer 2026
The expected base pay range for this position in the Toronto area is $45-$48/hour CAD
Ride sharing company
Be an early applicant
Ride sharing company
1001+ employees
Be an early applicant
The expected base pay range for this position in the Toronto area is $45-$48/hour CAD
1001+ employees
Company mission
To improve people’s lives with the world’s best transportation.
Role
Who you are
- Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences (Operations Research, Computer Science, Statistics, Applied Mathematics, Theoretical Physics, Behavioral Science, Electrical Engineering, etc.), Economics (Microeconomics Theory, Econometrics etc.), Data Engineering; or a related field; AND with a graduation date between December 2026 and June 2027 (required)
- Available during Summer 2026 for an internship in Toronto
- Experience coding in Python (required) or SQL, R; standard data science libraries (NumPy, Scikit-learn, PyTorch, TensorFlow, Keras); and ML Tools & Libraries (NumPy, SpaCy, NLTK, Scikit-learn, TensorFlow, Keras)
- Experimental design and analysis
- Exploratory data analysis
- Expertise in one of these specialties: optimization and mathematical modeling, machine learning fundamentals, or probabilistic and statistical modeling
- Bonus points: Experience in marketplace design, ridesharing, studying two-sided marketplaces, and/or transportation
What the job involves
- Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse
- They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment
- We are hiring for a variety of Data Science interns, focusing on the following specialties:
- Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app
- Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment
- Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems
- You will report into a Science Manager
- Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context
- Perform exploratory data analysis to gain a deeper understanding of the problem
- Write production modeling code; collaborate with software engineers to implement algorithms in production
- Design and run both simulated and live traffic experiments
- Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions
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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