At Lyft, community is who we are & its what we do. Its what makes us different. To create the best ride for all, we start in our own community by creating an open, inclusive, & diverse organization where all team members are recognized for what they bring.
As metropolitan cities grow, we aim to transform the way people commute within the city through becoming the leader in the development & operation of such vehicles. From bikes & scooters to future forms of transportation, you will be at the forefront of driving these new initiatives & revolutionize technology.
Data is at the heart of how Lyft makes business, product, & engineering decisions. The Lyft Bikes & Scooter (LBS) data science team is a specialized data science team which works collaboratively with partners across the organization, such as product, engineering, strategy & operations to develop business insights & make actionable recommendations. We are looking for passionate data scientists to come work alongside us to take on some of the most interesting & impactful problems in the future of ridesharing & autonomous vehicles.
LBS Data Scientists work in a fast paced & agile environment & pursue a variety of unique & challenging problems ranging from marketplace optimization & scooter placement, multimodality, product analytics, operations & policy analytics, & more. You will dig into the data to uncover insights, design experiments & measure the impact, & ultimately help influence decision-making across the entire organization.
- Own the product, hardware, marketplace, or behavioral analytics side of growing the scooter business
- Develop understanding & set business metrics that measure the health of our products, as well as passenger & driver experience
- Partner with product managers, engineers, marketers, designers, & operators to translate business insights into decisions & action
- Find opportunities for growth & efficiency for Lyft
- Design & analyze product experiments; communicate results & launch decisions
- Develop analytical frameworks to monitor business & product performance
Experience & Skills:
- Degree in a quantitative field like statistics, economics, applied math, operations research or engineering. Advanced degrees are preferred
- 4+ years of industry experience in a data science or analytics role
- Proficiency in SQL - able to write structured & efficient queries on large data sets
- Experience in programming, especially with data science & visualization libraries in Python or R
- Strong oral & written communication skills, & ability to collaborate with cross-functional partners to build the business