What are the responsibilities and job description for the Data Science Intern, Algorithms (Summer 2026) position at Lyft?
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:
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 3 days per week 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. #Hybrid
The expected base pay range for this position in the San Francisco area is $58-$62/hour USD. 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.
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
- Currently pursuing a Masters or PhD degree 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; with a graduation date between December 2026 and June 2027 (required)
- Available during Summer 2026 for an internship in San Francisco
- 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
- Great medical, dental, and vision insurance options
- Mental health benefits
- In addition to holidays, interns receive 2 days 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
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 3 days per week 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. #Hybrid
The expected base pay range for this position in the San Francisco area is $58-$62/hour USD. 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.
Salary : $58 - $62