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.