Data Scientist, Decisions - Mapping (Toronto)

Data Scientist, Decisions - Mapping (Toronto)

18 Oct
|
Lyft
|
Toronto

18 Oct

Lyft

Toronto

At the company, 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.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 protected, efficient, and seamless navigation for our rideshare drivers.Data Science is at the heart of the company'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 improve the quality of our map data in order to improve our recommendations?How do we benchmark and measure the success of our services?How do we validate features of the real world that affect our routing algorithms?Are we meeting our travel estimation promises to our customers?Responsibilities:Leverage data and analytic frameworks to identify opportunities for growth and efficiencyPartner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goalsDesign and analyze online experiments; communicate results andact 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 experienceIdentify and drive impact and alignment, shaping product and business strategy through data-centric presentationsExperiences:Degree in a quantitative field such as statistics, economics, applied math,



operations research or engineering (advanced degrees preferred), or relevant work experience1+ years experience in a data science role or analytics roleProficiency in SQL - able to write structured and efficient queries on large data setsEnd-to-end experience with data, including querying, aggregation, analysis, and visualizationExperience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, KerasExperience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholdersStrong oral and written communication skills, and ability to collaborate with and influence cross-functional partnersExperience in applying machine learning techniques a plus (e.G. reinforcement learning) to solve customer problems (e.G. personalization, segmentation)Experience working with ETL pipelines a plusBenefits:Extended health and dental coverage options, along with life insurance and disability benefitsMental health benefitsFamily building benefitsChild care and pet benefitsAccess to a the company funded Health Care Savings AccountRRSP plan with company match to help save for your futureIn addition to provincial observed holidays, salaried team members are covered under the company'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 servicethe company 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 the company ride creditsthe company is committed to creating an inclusive workforce that fosters belonging. the company 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. the company 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.the company 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. the company 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 the company offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #HybridThe expected base pay range for this position in the Toronto area is CAD $88,000 - CAD $110,000, 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.the company may use artificial intelligence to screen applicants, however, the company employees make the ultimate selection and hiring decisions.This job fills an existing vacancy.

📌 Data Scientist, Decisions - Mapping (Toronto)
🏢 Lyft
📍 Toronto

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