Data Science Manager, Risk

Fig is an award-winning, high-growth Canadian FinTech modernizing the world of consumer credit. We provide simple, accessible and fully digital personal loans, removing the complexity and delays of traditional lending to better serve Canadians.

Since launching in 2023, Fig has quickly built a strong reputation for innovation and customer trust. We have been named Consumer Lender of the Year by the Canadian Lenders Association and FinTech Startup of the Year by the FinTech Breakthrough Awards, and we are consistently recognized among Canada’s Best Workplaces. Our commitment to customers is reflected in our 4.8 out of 5 Trustpilot rating.

Backed by Fairstone Bank of Canada and Ontario Teachers’ Pension Plan, Fig combines deep lending expertise with the agility of a startup. This foundation allows us to effectively meet the evolving credit needs of Canadians across a wide range of financial backgrounds. 

We are looking for a hands-on, data-obsessed Data Science Manager, Risk to build and operationalize the models, data pipelines, and analytical frameworks that power our lending decisions. Reporting to the Director of Credit Risk, you will play a key role in advancing our credit risk capabilities through machine learning, data engineering, model governance, and data-driven experimentation. While this role does not include people management responsibilities in the short term, you will provide technical leadership by driving cross-functional initiatives, mentoring junior analysts, and championing best practices in data science and risk modeling.

You'll join an experienced team focused on Getting Stuff Done (#GSD), where curiosity, scientific rigor, and continuous innovation drive every decision. You'll work across the full model lifecycle from developing and deploying models to monitoring, governing, and continuously improving their performance. You should be comfortable navigating ambiguity, solving complex analytical problems, and translating insights into scalable, production-ready solutions.

This is an exciting opportunity to work across multiple data science disciplines, including credit risk model development, alternative labeling strategies, reject inference, model validation and quality assurance, feature engineering, model monitoring, production decisioning, and credit risk data engineering. You'll design robust data pipelines, improve model performance and governance, automate analytical workflows, and partner closely with Credit Strategy, Product, Finance, Growth and Engineering to deliver scalable, data-driven lending solutions. This is a newly created role, which means you’ll have the opportunity to help shape the mandate, build core processes, and make a visible impact as Fig continues to grow.

Culture matters deeply to us. You'll have the support of experienced colleagues across the organization who are passionate about solving challenging problems together. We're looking for someone who combines strong technical expertise with curiosity, collaborates effectively across teams, and thrives in an environment that values transparency, accountability, and continuous improvement.

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