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 are hiring motivated experts in each of these fields. We're looking for 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, community is what we are and it’s what we do. It’s what makes us different. To create the best ride for all, we start in our own community by creating an open, inclusive, and diverse organization where all team members are recognized for what they bring.

As a Data Science Intern on the Decisions: Inference track, you will work on designing and analyzing tests in our dynamic marketplace, estimating statistical and machine learning models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. We expect candidates to have strong probability skills and statistical rigor, knowledge of causal inference, and familiarity with advanced modeling techniques from fields such as econometrics, statistics, and machine learning.

You will report into a Science Manager.

Responsibilities:

Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
Perform exploratory data analysis to gain a deeper understanding of the problem
Construct and fit statistical and machine learning models
Write production modeling code; collaborate with engineers to implement algorithms in production systems
Design and conduct marketplace experiments in a setting with spatial interference patterns and time-varying treatment effects
Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions
Prototype modeling approaches that reduce error in estimators, leveraging high-dimensional marketplace activity data
Rigorously evaluate and compare policies based on models, using modern approaches such as off-policy evaluation

Experience:

Graduating with a PhD degree between December 2023 and June 2024
Currently pursuing a PhD degree in Statistics, Economics, Machine Learning, Biostatistics, or Computer Science, or a related field
Experience coding in Python, SQL, and standard data science libraries (NumPy, Scikit-learn, PyTorch, TensorFlow, Keras)
Experimental design and analysis of randomized experiments such as A/B tests
Probabilistic and statistical modeling
Exploratory data analysis
Bonus points: Experience in studying two-sided marketplaces

Benefits:

Great medical, dental, and vision insurance options
Mental health benefits
In addition to holidays, interns receive 1 day paid time off and 3 days sick time off
401(k) plan to help save for your future
Pre-tax commuter benefits
Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Benefits are available for Lyft team members who work 30 or more hours per week. Please request information about benefits available to team members who work 29 hours or less per week.

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

This role is work-from-anywhere in the U.S., excluding U.S. territories.

The base salary range for this position in the US is $47/hour - $61/hour. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.