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Lyft

Analytics Lead, SCC

Toronto, Ontario, Canada

Location
Toronto, Ontario, Canada
Work
Hybrid
Employment
Not stated
Level
Lead / staff
Function
Data & AI
Pay
From CA$96K a year (read from the ad)
Posted
3 months ago

About the role

At Lyft, 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.

The vision of the Safety & Customer Care (SCC) team is to foster long-term loyalty to Lyft with every support interaction. If we are successful, a Lyft customer will rarely interact with Lyft Support. But when that interaction occurs, their issue is resolved quickly, effectively, and with true care. For a Lyft customer, their experience of Support should be that “Lyft cares about me and made the experience easy.”

As a Data Analytics Lead, you’ll partner directly with cross-functional stakeholders to identify opportunities and design solutions for improving our customers’ support experience. You’ll leverage your analytical expertise to deliver actionable insights and recommendations to drive quality business decisions with customer-facing impact. The ideal candidate is a critical thinker and exceptional problem solver who can build strong relationships with different teams, and who is eager to serve as a leader within the broader Support organization to drive our business forward.

Responsibilities

  • Partner with Product, Engineering, Data Science & Analytics, Business Operations and other cross-functional stakeholders to achieve business goals
  • Develop frameworks and scalable processes to drive decision-making and prioritization
  • Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time
  • Design A/B tests and execute analyses to evaluate the impact of new product features and operational improvements
  • Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience
  • Monitor and diagnose KPI performance and present findings to senior leadership

Experience

  • Degree in a quantitative field like statistics, economics, applied math, operations research or engineering. Advanced degrees are preferred
  • 2+ years of hands-on technical experience in a data science role or equivalent analytical role in a high growth startup
  • Ability to translate unstructured business problems into clearly defined requirements with minimal oversight
  • Strong problem-solving and analytical skills with the ability to transition between detailed data and high-level business problems
  • Exceptional communication (listening, written, and oral) skills with the ability to present findings & recommendations targeted to the audience in question
  • Strong interpersonal skills, with the ability to build relationships and trust across functions and work collaboratively
  • Proficiency in SQL and Python with ability to independently break down large datasets and synthesize inputs from multiple sources

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

Lyft is committed to creating an inclusive workforce that fosters belonging. 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 if you wish to make such a request.

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

The expected base pay range for this position in the Toronto area is CAD $96,000 - CAD $120,000, 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.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Source

Posted by Lyft on their own hiring page, app.careerpuck.com. OptiTalent shows it as published, read 07 Nov 2026 01:07 UTC; the original is the reference.

View the original ad ↗

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