Analytics Lead

Lyft; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

A leading mobility company is seeking an Analytics Lead to shape the future of urban mobility. The ideal candidate will leverage data to enhance the performance of bikeshare and scooter markets across North America. Responsibilities include conducting deep analyses, developing scalable processes, and collaborating with cross-functional teams. Applicants should have strong data analytics experience, proficiency in SQL, and effective communication skills. Benefits include health coverage, flexible paid time off, and support for new parents.

Benefits

Extended health and dental coverage

Mental health benefits

Flexible paid time off

Child care benefits

Subsidized commuter benefits

Qualifications

• 3-5+ years experience in data analytics in a high‑growth environment.
• Experience in consulting, operations, or transportation/logistics preferred.
• Ability to produce data visualizations and build dashboards for performance analysis.

Responsibilities

• Conduct deep-dive analyses to root cause issues and propose solutions.
• Forecast operational requirements to maintain high service levels.
• Monitor performance and present findings to key stakeholders.

Skills

SQL

Quantitative analysis

Data visualization

Interpersonal skills

Communication skills

Problem-solving

Attention to detail

Product ownership

Sustainable mobility passion

Education

Bachelor's Degree or equivalent relevant professional experience

Tools

Python

Job 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 teams, as well as software and hardware engineering teams, to monitor the performance of and drive improvements in our hardware. You will also play a key role in monitoring and mitigating rideable theft and loss. You will work in a fast-paced environment where your analytical insights directly impact strategic decisions around operational processes, staffing, and product changes, ultimately driving better performance and long‑term investments in micromobility infrastructure.

We’re looking for a passionate and driven Analytics Lead 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, Data Science & Analytics, 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, drive decision‑making and prioritization
• Forecast operational requirements needed to maintain high service levels and meet contractual and financial targets
• Work closely with cross‑functional partners to deliver ongoing support and deep dive analyses on performance; monitor and diagnose performance and present findings to key stakeholders

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 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

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