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 chance to thrive.
Data Science & Analytics is at the heart of the company's products and decision-making. The Rider Experience team sits at the center of how millions of riders discover, choose, and return to the company. We are hiring a Data Science Manager to lead our Toronto-based science & analytics team that turns rider behavior into product strategy. This role owns the analytical foundation behind our most consequential rider-facing decisions: how we measure experience quality, where friction costs us retention, and which bets move rider LTV. You will set the measurement and experimentation standards for rider product squads, and translate ambiguous business questions into rigorous, decision-ready analysis that shapes roadmap and investment.
You will also lead the team's transition to AI-native data science and analytics workflows, embedding AI tooling into how we explore data, make decisions, and ship products.
Responsibilities: Lead and grow a high-performing team of data scientists and analysts with diverse backgrounds
Define and drive the data science vision, strategy, and roadmap, aligning with business and product objectives to improve market competitiveness and rider experience
Provide strong technical guidance and coaching to the team on complex data science problems
Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate insights into decisions and action
Lead deep-dive analyses into large-scale datasets to identify opportunities for improving rider app experience and overall rider product health
Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies
Mentor and guide the professional and technical development of your team members; help develop their careers and assign projects tailored to their skill levels, work styles, and professional goals
Maintain a balance between building sustainable, high-impact projects and shipping quickly
Lead the team in adopting AI-native data science and analytics workflows, embedding AI tooling across data exploration, modeling, and insight delivery




Partner with the the company recruiting team to hire high-potential candidates from diverse backgrounds
Experience: Advanced degree (MS or PhD) in a quantitative field such as Statistics, Applied Mathematics, Economics, Computer Science, or a related area
Hands-on technical experience in experimentation, causal inference, or data science, preferably with applications in machine learning or marketplace dynamics
2+ years of management experience building, leading, and mentoring data science teams
Strong expertise in statistics, experimental design, and causal inference, including A/B testing, multivariate testing, and incremental lift measurement
Strong data storytelling and influence skills, with experience presenting insights and recommendations to senior leaders
Experience launching and monitoring consumer-facing products and iterating through data-driven experimentation and metrics analysis
Experience guiding teams through ambiguous, complex technical challenges to deliver impactful solutions
Experience building or operationalizing machine learning models (e.g., propensity, segmentation, churn, personalization) in partnership with engineering
Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences
Benefits: Extended health and dental coverage options, along with life insurance and disability benefits
Mental health advantages
Family building benefits
Child care and pet benefits
Access to a the company 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 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 service




the 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 credits
the 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. #Hybrid
The expected base pay range for this position in the Canada area is CAD $172,000 - CAD 215,000, 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.

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📌 Data Science Manager, Rider Experience (Ontario)
🏢 United States Digital Space
📍 Ontario