Data Scientist, Algorithms - Rider Pricing

Posted 18 Hours Ago
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Toronto, ON
Entry level
Transportation
The Role
As a Data Scientist in the Rider Pricing team at Lyft, you will analyze data to identify growth opportunities, develop metrics and dashboards, and design online experiments to enhance decision-making. You will collaborate with cross-functional teams, providing insights that influence pricing strategies and enhance rider and driver experiences.
Summary Generated by Built In

At Lyft, our purpose is to serve and connect. 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. Data Scientists at Lyft work in dynamic environments, where we embrace moving quickly to build the world’s best transportation. We take on a variety of problems ranging from shaping long-term business strategy with data, making short-term critical decisions, and building algorithms/models that power our internal and external products. 

As a Data Scientist, you will be developing analyses, metrics, dashboards, and mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We are hiring motivated experts in each of these fields. We're looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment.

We are looking for a Data Scientist to join the Rider Pricing team. The Pricing team owns the models and software systems that determine the prices shown to riders. Working with our business and analytics partners, the team owns tools to ensure Lyft offers competitive prices while making efficient financial trade-offs. Additionally, the team owns the development and maintenance of real-time and planned rider incentives with a goal of driving efficient ride growth. The team uses a wide range of causal inference, optimization and reinforcement learning methodologies to achieve these goals.

You will report to a Data Science Manager.

Responsibilities:

  • Leverage data and analytic frameworks to identify opportunities for growth and efficiency 
  • Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action
  • Design and analyze online experiments; communicate results and act on launch decisions
  • 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
  • Provide coaching and technical guidance for the team
  • Prioritize and lead deep dives into our data to uncover new product and business opportunities
  • Facilitate and foster data-driven and informed decision making and prioritization

Experience:

  • Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields or related work experience. 
  • Passion for solving unstructured and non-standard, ambiguous mathematical problems by leveraging expertise in one or multiple fields.
  • Strong skills in optimization, statistics, and causal inference. 
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization.
  • Proficiency with Python, or another interpreted programming language like R or Matlab
  • Strong communicator. Able to coordinate with several teams of data scientists to deliver on complex initiatives. 
  • Strong business sense and understanding of experimentation methodologies.
  • Proficiency in SQL - able to write structured and efficient queries on large data sets.
  • Experience in online experimentation and statistical analysis.
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners.

Benefits:

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

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.

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. #Hybrid

Top Skills

Matlab
Python
R
The Company
HQ: San Francisco, CA
22,282 Employees
On-site Workplace

What We Do

Lyft was founded in 2012 by Logan Green and John Zimmer to improve people’s lives with the world’s best transportation, and is available to approximately 95 percent of the United States population as well as select cities in Canada. Lyft is committed to effecting positive change for our cities by offsetting carbon emissions from all rides, and by promoting transportation equity through shared rides, bikeshare systems, electric scooters, and public transit partnerships.

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