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.

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

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.

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 in mathematical sciences at a university in Mexico, with a graduation date between December 2024 and Summer 2025 (Computer Science, Operations Research, Electrical Engineering, Data Engineering, Statistics, Applied Mathematics, Theoretical Physics, Behavioral science, etc. or a related field) - required
• Experience coding in Python or R, SQL; 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

This role will be in-office on a hybrid schedule if an established Lyft Location is available to the Mexico City region — Hybrid Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day.