# Data Science Intern, Algorithms (Summer 2027 - Toronto)

**Company**: Lyft
**Location**: Toronto, ON
**Job type**: internship
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/lyft/jobs/8767697002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_540dd376-e98

## Description

Lyft's Data Science Team builds mathematical models that underpin the platform's core services. You will work on diverse problems, including optimization, prediction, modeling, inference, transportation, and mapping.

As a Data Science Intern, you will report to a Science Manager and work on one of the following specialties:

- Optimization: Construct and fit statistical or optimization models for automated decision-making.

- Machine Learning: Design, build, tune, and deploy machine learning models with a focus on feature engineering and deployment.

- Inference: Design and analyze tests, estimate statistical and ML models, and develop algorithmic policies.

Responsibilities:

- Collaborate with Engineers, Product Managers, and cross-functional partners to frame problems.

- Perform exploratory data analysis to understand the problem.

- Write production modeling code and implement algorithms with software engineers.

- Design and run simulated and live traffic experiments.

- Analyze experimental and observational data and communicate findings.

Experience:

- Pursuing a Master's or PhD degree in a relevant field (mathematical sciences, economics, data engineering).

- Available for an internship in Toronto during Summer 2027.

- Experience coding in Python, SQL, R, and familiarity with data science libraries.

- Expertise in one of the specialties: optimization and mathematical modeling, machine learning fundamentals, or probabilistic and statistical modeling.

Benefits:

- Mental health benefits.

- Paid time off and sick leave.

- Subsidized commuter benefits and Lyft ride credits.

## Skills

### Required
- Python
- SQL
- R
- data science libraries
- optimization
- machine learning
- inference
- experimental design
- exploratory data analysis

### Nice to have
- marketplace design
- ridesharing
- two-sided marketplaces
- transportation

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/lyft/jobs/8767697002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)