Description
About the roleThis is the most important technical hire we'll make this year, and one of the rare data science roles where you get to build an entire discipline from zero.
We're launching a line of flex payment products for your largest bills. These products are the foundation of something much larger: they're how Chexy builds the underwriting and credit muscle that will eventually power our full financial ecosystem. There is no playbook here yet. You'll write it.
You'll own credit and underwriting end to end: the models, the policy, the risk appetite, the decisioning logic, and the data infrastructure that feeds all of it. And you'll do it sitting on top of a dataset almost no one else in Canada has: how hundreds of thousands of Canadians actually pay their largest recurring bills, month after month. That's underwriting signal our competitors can't buy.
You won't be handed a risk framework and asked to maintain it. You'll build the credit brain of the company, which means hands on the data, hands on the models and then head up the function as it grows. If you want a role where the decisions you make show up directly in approval rates, loss curves, and a product roadmap that runs all the way to a credit card, this is it.
What you'll own- The credit and underwriting function from the ground up: strategy, models, policy, and the team that follows
- Underwriting and decisioning models for Rent Flex and every Flex product after it, built and deployed in production
- The credit data layer: defining the features, signals, and infrastructure that turn Chexy's payment data into underwriting power
- Risk appetite and credit policy - approval logic, limit assignment, pricing inputs, and the guardrails that keep losses where they should be
- Loss forecasting, portfolio monitoring, and the early-warning systems that tell us when something's moving before it shows up in the numbers
- Cross-functional partnership with Product and Engineering to ship decisioning into the live product, and with Compliance and our banking partners to keep it sound and regulator-ready
- The metrics that matter - approval rate, loss rate, model performance - owned by you, monitored by you, defended by you
Who you are- 6+ years in data science, with deep, hands-on experience building credit risk, underwriting, or decisioning models: ideally in lending, BNPL, cards, or fintech
- You've shipped models into production and you've watched them perform (or misbehave) against real money
- Fluent in Python and SQL, comfortable living in the data warehouse (we run on BigQuery) and turning messy data into decisions
- You understand the full credit lifecycle: acquisition scoring, underwriting, limits, loss forecasting
- A genuine 0-to-1 builder: you can stand up a function from nothing, set the strategy, and still write the code yourself
- Analytical enough to own your outcomes: you don't need someone else to tell you whether a model is working
- Familiarity with the Canadian credit ecosystem (Equifax, TransUnion) and the regulatory environment around lending is a strong plus
Note: this position is fully onsite at our downtown Toronto office, 5 days a week.
