Data Scientist, Decisions - Verticals

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.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, recommending and implementing technical solutions, designing experiments, shaping team priorities, and measuring the impact of new features.

The Verticals team encompasses 3 critical and unique products / marketplaces within Lyft: airports, scheduled rides, and events. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experiences and have unique considerations and dynamics. Scheduled rides allow riders to book a ride in advance with high reliability, and enable drivers to add structure to their work schedule. Lastly, events such as concerts or sporting games require similar considerations of special operations to ensure a seamless experience for both riders and drivers. 

As a Data Scientist on the Verticals team, you will collaborate with engineering, product, design, and operations to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as:

• How can we efficiently match riders and drivers together in these unique marketplaces, to minimize ETAs and improve the driver experience? 
• Are we able to forecast ride demand and implement driver guidance to ensure riders can rely on Lyft for an event ride?
• What is the most helpful way to display ride information to drivers so they can make informed decisions?
• What rider segments should we target with ride incentives to grow our marketshare for these verticals? 

• →Construct and fit statistical or optimization models to make production decisions such as changes to how we match riders and drivers; focusing on model proposal and offline model development 
• →Leverage data and analytic frameworks to identify opportunities for growth and efficiency, recommending technical solutions to drive business impact 
• →Design and analyze online experiments, including communicating results, acting on launch decisions, and recommending next steps based on learnings
• →Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action
• →Develop analytical frameworks to monitor business and product performance, leveraging experiments and causal inference
• →Establish metrics that measure the health of our products, the business, as well as the driver experience

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years of industry experience in a data science, analytics, or management consulting role
• Proficiency in SQL and Python
• Ability to perform technical experiments, including user split, time split, and region split
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Ability to manage, influence, negotiate, and inspire others in a fast-moving environment
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners