Senior Data Scientist, Finance & Market Risk
WealthsimpleRemote (Canada)Posted 19 March 2026
Tech Stack
Job Description
Senior Data Scientist, Finance & Market Risk
BUILD SOMETHING PEOPLE LOVE
Wealthsimple's mission is to help everyone achieve financial freedom – by making financial services simple, transparent, and low-cost. We're Canada's largest fintech, trusted by over 3 million clients with more than $100 billion in assets. We move fast, we own our work, and we care deeply about the people using our products. If that sounds like you, keep reading.
We're proud of what we've built — and we're just getting started. Read our Culture Manual https://www.wealthsimple.com/en-ca/culture and learn more about how we work https://www.wealthsimple.com/en-ca/careers.
ABOUT THE TEAM
The Finance and Market Risk Data Science team is a dynamic group of data scientists and analytics developers who deliver high-quality financial metrics and advanced analytics that drive key decisions at Wealthsimple. We support financial planning, treasury operations, liquidity management, and brokerage risk assessment for products like margin trading and options.
ABOUT THE ROLE
Our team has created a solid foundation for data-driven financial decision-making. Now we're ready to scale these initiatives, optimizing financial resources and enhancing risk management as our product offerings grow increasingly sophisticated. As the Senior Data Scientist, Finance & Market Risk, you'll make a significant impact through advanced analytics that support both strategic financial planning and sophisticated risk management across our expanding brokerage services.
WHAT YOU'LL DO
- Apply advanced analytics techniques to solve complex business problems across finance and market risk domains.
- Develop and maintain the finance data mart, with a focus on optimizing data quality, accessibility, and efficiency.
- Create insightful dashboards to monitor financial KPIs, profitability metrics, and regulatory reporting requirements.
- Collaborate cross-functionally with finance, risk, and product teams to provide business intelligence support for financial reporting, product performance analysis, and forecasting.
- Productionize and make continuous improvements to Wealthsimple’s machine learning models, ensuring that models are well tested, documented and maintained.
- Build automation tools and pipelines to increase team efficiency and scalability.
- Design and execute product experiments to help improve Wealthsimple’s client experience.
- Translate analytical findings into actionable business solutions.
- Build and enhance data assets that support a variety of analytics tasks across the business.
- Believe that simple is better, Occam's razor is your friend.
- Take ownership and ship it; release incrementally and iteratively.
- Teach and learn from your teammates. We value making others successful.
SKILLS YOU BRING
- Strong technical skills in coding (SQL & Python) and statistical methods.
- Strong understanding of data visualization principles and methodologies, including analytics engineering.
- Able to build and maintain multi-functional relationships with various teams across the business.
- Experience working with financial ledger data, including understanding of accounting principles, transaction flows, and reconciliation processes to ensure data accuracy and integrity
- Experience in building end-to-end productionized machine learning pipelines.
- Comfortable with software engineering best practices such as unit testing and version control.
- Results-driven: keeping things as simple as possible to achieve the product goals.
- Curiosity: willing to dive deep into product strategies and business context.
- Experience in complex experimental design (A/B tests, factorial design).
- Experience working in finance and risk management domain is a plus.
WHY WEALTHSIMPLE?
🌸 Top-tier health benefits and life insurance
📈 Long-term group savings with employer match, through Wealthsimple for Business
🌴 20 vacation days, 4 wellness days, and unlimited sick and mental ... (truncated, view full listing at source)
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