
About Lyft
The friendly ride-sharing alternative to Uber
Key Highlights
- Headquartered in San Francisco, CA
- Over 100 million rides completed
- $4.9 billion raised in funding
- Acquired PBSC Urban Solutions in 2022
Lyft, headquartered in San Francisco, CA, is a leading ride-sharing company focused on improving transportation experiences in the U.S. and Canada. With over 100 million rides completed and $4.9 billion raised in funding, Lyft aims to provide a more reliable and environmentally friendly alternative ...
🎁 Benefits
Lyft offers a comprehensive benefits package including unlimited paid time off for salaried employees, 15 days PTO for hourly team members, and 18 wee...
🌟 Culture
Lyft fosters a culture focused on reliability and friendliness, positioning itself as a greener alternative to Uber. The company emphasizes local oper...
Skills & Technologies
Overview
Lyft is hiring a Data Scientist - Algorithms to enhance production algorithms for driver pay. You'll leverage machine learning and optimization skills in Seattle. This position requires a strong background in data analysis and statistical modeling.
Job Description
Who you are
You hold an M.S. or Ph.D. in a quantitative field, showcasing your strong analytical skills and deep understanding of data science principles. You have experience in machine learning and optimization, allowing you to design and implement effective algorithms that drive business decisions. Your background includes performing exploratory data analysis, which has equipped you with the ability to frame complex problems both mathematically and in a business context. You are proficient in Python and have experience writing production-level code, collaborating closely with software engineers to implement algorithms effectively.
You possess excellent communication skills, enabling you to convey complex findings to both technical and non-technical stakeholders. You thrive in cross-functional teams, partnering with engineers, product managers, and business partners to ensure alignment on project goals. Your experience includes designing and running experiments, both simulated and live, to validate your models and inform decision-making. You are detail-oriented and committed to continuously monitoring policy performance in production, ensuring that your contributions have a measurable impact on company metrics.
What you'll do
As a Data Scientist - Algorithms at Lyft, you will be responsible for creating and refining algorithms that determine driver pay, directly impacting the earnings of Lyft drivers. You will collaborate with cross-functional teams to frame problems and develop solutions that align with business objectives. Your role will involve performing exploratory data analysis to gain insights into pay policies and their effectiveness. You will design and fit statistical, machine learning, or optimization models to enhance the accuracy and fairness of driver compensation.
You will write production modeling code and work closely with software engineers to implement your algorithms in a live environment. Your responsibilities will also include designing and conducting both simulated and live traffic experiments to test the effectiveness of your models. Analyzing experimental and observational data will be crucial, as you will need to communicate your findings clearly to facilitate launch decisions. Your work will contribute to key company metrics, including profit, rides completed, driver sentiment, and pickup reliability, making your role vital to Lyft's mission.
What we offer
Lyft offers a competitive salary range for this position in the Seattle area, between $128,000 and $160,000, not including potential equity offerings, bonuses, or benefits. We foster a work environment where all team members belong and have the opportunity to thrive, emphasizing collaboration and innovation. You will be part of a dynamic team that values your contributions and encourages professional growth. We believe in the importance of work-life balance and provide flexible working arrangements to support our employees' well-being.
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