Quantitative Risk Modeler

About the team

Operations is the team that makes everything run. Within Operations, the Credit Risk team owns the models, frameworks, and day-to-day execution that keep Wealthsimple's brokerage business running soundly — across margin, delinquency, and dynamic risk reporting. We're a high-ownership team that works closely with Product, Finance, and the business to close gaps, reduce friction, and build for scale. If you take risk seriously and want your work to have a direct impact on how millions of Canadians experience their finances, you'll feel at home here.

About the role

We manage billions of dollars on behalf of millions of Canadians, and doing that well means having people who understand not just what a model says — but whether it's saying something meaningful. This is a risk quant role in the true sense: you'll own the development, maintenance, and methodology of the models our teams depend on to make consequential decisions every day. You'll work across margin, stress testing, and capital impact modelling in a CIRO-regulated environment, and you'll be the person who knows when something is off and can fix it.

What you'll do

• Own the development, testing, and ongoing maintenance of quantitative risk models, including VaR, SVaR, broad-based stress testing, and single-stock stress testing — updating them as market conditions and regulatory requirements evolve

• Write and maintain clear methodology documentation for every model used in day-to-day stakeholder decisions, so the teams consuming your outputs understand what they're working with

• Apply deep knowledge of CIRO 5000 margin rules to model how margin requirements and capital would be impacted under a range of stressed conditions

• Develop production-quality code across multiple programming languages to build, maintain, and improve model infrastructure

• Work cross-functionally with margin, delinquency, and dynamic risk reporting teams to support risk-cognizant decision-making — translating complex model outputs into clear, actionable guidance

• Identify and flag model performance issues proactively, including cases where outputs may be inaccurate or non-meaningful given current market conditions

Skills you bring

• 7 to 10 years of experience in a quantitative risk or quantitative analytics role within financial services, preferably in a CIRO-regulated brokerage environment

• Genuine hands-on model development experience across stress testing methodologies including VaR, SVaR, broad-based stress testing, and single-stock stress testing — not just model consumption

• Deep knowledge of markets, trading instruments, and valuation principles across equities, options, futures, and fixed income

• Deep understanding of CIRO 5000 margin rules and the ability to model how margin requirements and capital would be impacted under stressed conditions

• Expert-level proficiency in at least one quantitative programming language (Python, R, or similar), with demonstrated ability to develop production-quality code

• Strong written communication skills, including the ability to produce clear methodology documentation for both technical and non-technical audiences

• Ability to work independently on complex technical problems and deliver under tight deadlines without requiring hands-on management through the work

• Ability to lead a small team. Depending on the candidate's qualifications/skills, they may be evaluated for a Senior Manager position.

Nice to have

• Master’s degree in a quantitative field.

• CFA, FRM, or equivalent professional designation

• Derivatives Fundamentals and Options Licensing (DFOL) certification

• Familiarity with building or contributing to model governance frameworks, including ticketing, prioritization, and model registry infrastructure

• Experience presenting quantitative model outputs and methodology to senior stakeholders or regulators

• Exposure to margin lending, portfolio lending, or credit risk in a brokerage context

Who you are

• Someone who understands market context deeply enough to know when a model is producing results that don't make sense — and experienced enough to fix it

• Rigorous about methodology and documentation; you don't consider something done until the next person can understand it without asking you

• Comfortable working independently on hard technical problems; you don't need to be managed through the work, and you know how to prioritize when deadlines are real

• A clear, direct communicator who can bring non-technical stakeholders along without losing precision

• Thoughtful about how you use new tools, including AI — you see them as ways to work better, not as substitutes for the judgement this work requires

• Someone who builds trust with cross-functional partners by being reliable, consistent, and easy to work with even when the subject matter is complex