188K–283K CAD / year
Staff Product Manager, Risk
ProductHybrid — Toronto, Canada
Published on 2026-10-28
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
Lead major initiatives across Stripe’s Risk organization and other Stripe teams, from defining ambiguous problems through delivery and adoption. Shape risk infrastructure and product direction, including how data and AI are used to identify and mitigate risk at scale.
About the company
Stripe provides payment infrastructure and financial tools that help businesses accept payments, manage subscriptions, and move money globally. It serves startups through large enterprises with APIs for online and in-person commerce.
The team
Risk & Financial Crimes
Stack
AIMachine learningAPIsData infrastructure
What you'll do
- Identify cross-team opportunities and set clear product and technical direction with measurable outcomes.
- Lead cross-Risk and cross-Stripe initiatives through delivery, adoption, and iteration.
- Advance the use of data and AI to identify and mitigate risk at scale.
- Partner with engineering, data science, and machine learning leaders on architecture, data foundations, models, APIs, and product experiences.
- Build alignment across teams and guide reusable Risk capabilities.
What we're looking for
- Track record delivering high-impact initiatives across multiple teams or organizations.
- Ability to clarify ambiguous problems and drive work through execution and adoption.
- Strong technical judgment across data, AI, machine learning, APIs, platforms, and system architecture.
- Experience shaping technical direction and product strategy with senior leaders.
- Strong quantitative skills, including data analysis and causal reasoning.
- Ability to influence senior stakeholders and lead without formal authority.
- Excellent written and verbal communication; high agency and a hands-on, low-ego approach.
Nice to have
- Engineering background, preferably focused on machine learning.
- Experience applying AI or machine learning to high-stakes problems at scale.
- Experience in fraud, credit, payments, financial services, or trust and safety.
- Experience working with globally distributed teams.
Benefits
- Equity
- Company bonus
- Retirement plans
- Health benefits
- Wellness stipends