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.
As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. 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:
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, Wednesdays, and Thursdays. 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. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
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At Lyft, we believe in connecting communities and providing safe, efficient rideshare experiences. We are currently on the lookout for a driven Data Scientist to join our Mapping team in Toronto, Canada. In this role, you will collaborate with a world-class team of engineers, product managers, and designers to enhance the quality of our mapping products. Your analytical expertise will directly impact our recommended routes and travel time estimations, ensuring they are as accurate as possible for our drivers. Imagine diving deep into our spatial data to identify opportunities for growth and efficiency in routing—this is where you will shine! As a Data Scientist at Lyft, you'll leverage data to shape our business decisions, identify key metrics for performance, and validate critical features affecting our routing algorithms. You will be at the core of problem-solving, addressing questions like how to enhance our map data quality and how to measure the success of our services. Your role will involve designing experiments and communicating results effectively to influence cross-functional partners. We're looking for someone with a quantitative background, solid experience in data science, and proficiency in SQL, Python or R, with a knack for applying machine learning techniques. If you're passionate about data and ready to implement your insights into actionable solutions in a fast-paced environment, we want to meet you at Lyft!
Lyft is one of the leading ride-sharing companies in America offering services in ride-hailing, vehicles for hire, motorized scooters, a bicycle-sharing system, rental cars, and food delivery in the United States and select cities in Canada.
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