Data Science Intern, Algorithms (Summer 2027)

Lyft

Toronto

Hybrid

CAD 62,000 - 66,000

Full time

14 days+
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Benefits offered by this job

Mental health benefits
Paid time off
Sick time off
Commuter benefits
Ride credits

Job summary

Lyft is seeking Masters/PhD students for Data Science internships in Toronto. You will work on optimization, ML, and inference problems across the marketplace, reporting to a Science Manager. Ideal candidates are pursuing advanced degrees in mathematical sciences with strong Python/SQL/R skills and hands-on DS library experience.

The role is in-office on a hybrid schedule, requiring at least 3 office days weekly. CAD 45–48 per hour base pay, with benefits and a collaborative environment.

Qualifications

  • Currently pursuing a Masters or PhD in Canada (required).
  • Graduation date between December 2027 and June 2028 (required).
  • Available Summer 2027 for an internship in Toronto.
  • Experience coding in Python, SQL, or R and using standard DS libraries.

Responsibilities

  • Frame problems mathematically and with business context.
  • Perform exploratory data analysis to understand issues.
  • Write production modeling code and collaborate with engineers.
  • Design and run simulated and live traffic experiments.
  • Analyze data and communicate findings to partner teams.

Skills

Python programming
SQL
R
Exploratory data analysis
Experimental design

Education

Masters or PhD in mathematical sciences or related field

Tools

NumPy
Scikit-learn
PyTorch
TensorFlow
Keras
SpaCy
NLTK

Job description

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.

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.

Responsibilities:
  • 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
Experience:
  • 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 witha graduation date between December 2027 and June 2028 (required)
  • Available during Summer 2027 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
Benefits:
  • Mental health benefits
  • In addition to holidays, interns receive 2 days paid time off and 3 days sick time off
  • 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 office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in‑office perks Lyft offers.

The expected base pay range for this position in the Toronto area is CAD $45 - CAD $48 per hour. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

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