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?
Responsibilities:
- 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
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
Benefits:
- Extended health and dental coverage options, along with life insurance and disability benefits
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- RRSP plan with company match to help save for your future
- In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
- Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
- Subsidized commuter benefits and Lyft ride credits
Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. 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.
Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.
This job fills an existing vacancy.