Job description
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 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, 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.
As a Data Science Intern on the Algorithms: Machine Learning track, you will have the opportunity to drive meaningful impact at Lyft by designing, building, tuning, and deploying machine learning models that make our rider and driver experience reliable and enjoyable. Working alongside product managers and engineers, you will learn the ins and outs of our ecosystem of data, services, models, and products.
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
- Feature engineering
- Design, implement, and test machine learning models
- Write production modeling code; collaborate with software engineers to implement your models 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 (Operations Research, Electrical Engineering/Computer Science, Statistics, Control Theory, Applied Mathematics, Theoretical Physics), Economics (Microeconomics Theory, Econometrics, Labor), Behavioral Sciences (Marketing Science, Behavioral Psychology), Machine Learning or NLP, Data Engineering; or a related field
- Experience coding in Python or R, SQL, NLP, and ML Tools & Libraries (NumPy, SpaCy, NLTK, Scikit-learn, TensorFlow, Keras)
- Experimental design and analysis
- Expertise in Machine Learning fundamentals
- Bonus points: Experience in marketplace design, ridesharing, and/or transportation
Benefits:
- Great medical, dental, and vision insurance options
- 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
Lyft is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Lyft does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Lyft will also consider for employment qualified applicants with arrest and conviction records.
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About this role
Apply before
May 1st, 2021
Job posted on
November 16th, 2020
Job type
Intern
Hiring timezones
Lyft is hiring for this role in the following timezones:
UTC -11.0
UTC -10.0
UTC -9.5
UTC -9.0
UTC -8.0
UTC -7.0
UTC -6.0
UTC -5.0
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UTC +12.0
UTC +12.75
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UTC +14.0
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About the company
Ride by ride, we’re reimagining the world’s best transportation. We envision a world where cities feel small again. Where transportation and tech bring people together, instead of apart. We see the fu...We'll keep you updated when the best new remote jobs pop up.
