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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.As a Data Scientist on the Map Experience team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve Lyft’s in-house mapping product, Lyft Maps. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including: How do we design a frictionless navigation experience for rideshare drivers? Are drivers able to follow our guidance? How can we categorize and prioritize navigation issues on our platform? What defines a good pick-up experience between a rider and a driver? How do we benchmark and measure the success of map services? 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 actionDesign and analyze online experiments; communicate results and act on launch decisionsDevelop analytical frameworks to monitor business and product performanceEstablish metrics that measure the health of our products, as well as rider and driver experience Experience Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience1-2 years of industry experience in a data science or analytical role Proficiency in SQL - able to write structured and efficient queries on large data setsExperience in programming, especially with data science and visualization libraries in Python or RExperience in online experimentation and statistical analysisStrong 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 benefitsMental health benefitsFamily building benefitsAccess to a Health Care Savings AccountIn 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 hire10 paid sick days per year regardless of province18 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 following the establishment of a Lyft office in Toronto — 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.