Analytics Lead, LUS
Lyft
| Company | Lyft |
| Category | Data & Analytics |
| Location | Toronto |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 9 Jan 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
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.
Data and analytics are at the heart of Lyft's products and decision-making. As a member of the Lyft Urban Solutions team, you will play a key role in shaping the future of bikeshare by leveraging data to improve the performance of our bikeshare and scooter markets across America. A successful candidate thrives in a dynamic and collaborative environment, has a natural curiosity, and isn’t afraid to dive deep.
In this role, you will collaborate closely with Operations, Policy, Engineering, Product and Finance teams to drive data-informed strategies that align our operations and products with city transportation goals and user needs. You will work in a fast-paced environment where analytical insights directly impact decisions ranging from fleet management and operations performance to pricing and product features to long-term investments in bikesharing infrastructure.
We’re looking for a passionate and driven Data Analyst to tackle some of the most complex and impactful challenges in micromobility. If you’re excited about shaping the future of urban mobility through data, we’d love to hear from you.
Responsibilities:
Partner with Product, Engineering, Policy, Operations, Finance and other cross-functional stakeholders on initiatives to conduct deep-dive analyses to root cause issues and propose solutions
Develop frameworks, business logic and scalable processes to streamline reporting and drive decision-making
Forecast operational requirements needed to maintain high service levels and meet contractual and financial targets
Work closely with cross-functional partners to deliver data quickly, reliably and accurately to our city partners
Monitor and diagnose KPI performance and present findings to senior leadership
Experience:
3-5+ years experience in data analytics in a high-growth environment, preferably a consulting, operations or transportation / logistics space
Bachelor's Degree or equivalent relevant professional experience
Highly skilled in SQL and quantitative analysis, you can deep dive into large amounts of data, draw meaningful insights, dissect business issues and draw actionable conclusions
Ability to develop scalable approaches and produce data visualizations to drive business insights and provide tangible solutions; experience building dashboards for performance analysis is a plus
Extreme comfort working with ambiguity. Ability to translate unclear issues or unstructured problems into clearly defined requirements with minimal oversight
Strong interpersonal skills, with the ability to build relationships, trust and influence with cross-functional partners
Great communication (listening, written, and oral) skills with the ability to present findings & recommendations targeted to the audience in question
Strong attention to detail, structured thinking and experiences developing processes to reduce human error
Adept at contextualizing real world operations into analytical problem solving
A strong sense of product ownership - you’re constantly looking for ways to improve the customer’s experience and aren’t afraid to get your hands dirty to do so
Passionate about sustainable mobility and active transportation
Bonus: Proficiency in Python and associated data science libraries
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 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 te
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