Data Science, Metrics

Job Title: Data Science, Metrics Company: Lyft Job Category: Data Science Roles & Responsibilities: Data and analytics are at the heart of Lyft's products and decision\-making. The Metrics team sits in the Central Market Management organization and owns the business metrics that leaders use to run the marketplace. We define these metrics, build and manage the tools and dashboards that make them reliable and easy to access, and drive consistent, standardized definitions across the organization. We are looking for a Data Scientist to join the Metrics team and help shape Lyft's products and decision\-making. You will own a domain within the team's surface area, building and maintaining the data and metrics that leaders and partner teams rely on, with significant executive exposure along the way. We want an intellectually curious person with strong attention to detail, a track record of analytical problem\-solving, and skilled communication. You will report to a Data Science Manager. Responsibilities * Own one or more domain datasets end\-to\-end, from source data through to the metrics that consumers rely on * Build and maintain the processing logic and pipelines that turn raw inputs into trusted, analysis\-ready data * Own the business metrics derived from that data, developing the deep understanding of the source needed to build each metric correctly * Ensure the data is accurate, consistent, and reliable, with quality checks that catch problems before consumers see them * Deliver data and metrics to stakeholders in a usable form, and support them as they integrate it into their decisions * Partner with product managers, engineers, and operators to translate the data into decisions and action * Communicate findings to stakeholders in a clear and concise manner Lyft 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. Lyft 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 Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. \#Hybrid Work Location: Toronto, Ontario, Canada Availability: Full time

Experience * Degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering (advanced degrees preferred), or relevant work experience * 3\+ years of industry experience in a data science or analytics role * Proficiency in SQL, with the ability to write structured and efficient queries on large datasets * Programming experience, especially with data science and visualization libraries in Python or R * Strong oral and written communication skills, and the 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 * Child care and pet benefits * Access to a Lyft funded Health Care Savings Account * RRSP plan with company match to help save for your future * In addition to provincial observed holidays, salaried team members are covered under Lyft'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 service * Lyft 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 Lyft ride credits The expected base pay range for this position in the Toronto area is CAD $108,000 \- CAD $135,000, 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. Key Skills: Data Science Salary: $108,000