Data Science Intern, Algorithms (2024)

Key Skills

Algorithms, Behavioral science, Data Analysis, Data science techniques, Keras software library, Machine learning techniques, NumPy, Optimization, Python Programming, PyTorch, R Programming, Scikit-learn, SQL, TensorFlow

Job Description

At Lyft, community is what we are and it’s what we do. It’s what makes us different. To enable 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.

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

Experience:

• Graduating with a Masters or PhD degree between December 2024 and June 2025
• Currently pursuing a Masters or PhD degree in mathematical sciences (Operations Research, Electrical Engineering/Computer Science, Statistics, Applied Mathematics, Theoretical Physics, Behavioral science etc.), Economics (Microeconomics Theory, Econometrics etc.), Data Engineering; or a related field
• 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

Benefits:

• 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

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. 

Starting in September 2023, 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, Thursdays and a team-specific third day.

The expected range of pay for this position in the San Francisco Bay Area, Seattle, and NYC areas is $54-$62/hour USD. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.