Data Scientist, Decisions - Rider

Data Scientist, Decisions, Rider

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. As a member of the Rider Science team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products. We’re looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems in ridesharing.

As a Data Scientist, Decisions in the Rider team, you will leverage data and rigorous, analytical thinking to shape our rider app and make business decisions that put our customers first. You will identify and scope opportunities, shape priorities, recommend technical solutions, design experiments, and measure impact. You will bring a quantitative mindset to decision-making in partnership with product, design, engineering, business, and operations stakeholders throughout the organization.

You will report to a Data Science Manager in the Rider team.

Responsibilities:

• Leverage data and analytic frameworks to identify opportunities for growth and efficiency
• Develop analytical frameworks to monitor business and product performance
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Design and analyze online experiments; communicate results and act on launch decisions
• Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action

Experience:

• Experience in statistical analysis (experience in online experimentation preferred)
• Experience in programming, especially with data science and visualization libraries in Python or R is helpful
• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 1-2 years of industry or project experience in solving data science or analytics problems
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners

Benefits:

• Access to a Health Care Savings Account
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• 4 Floating Holidays each calendar year prorated based off of date of hire
• Mental health benefits
• 10 paid sick days per year regardless of province
• Extended health and dental coverage options, along with life insurance and disability benefits
• In addition to provincial observed holidays, team members get 15 days paid time off, with an additional day for each year of service
• Family building benefits

Lyft proudly pursues and hires a diverse workforce. 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 now if you wish to make such a request.

Starting in September 2023, this role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.