Wealthsimple is hiring a Sr Data Scientist Finance in Toronto!
Wealthsimple, a Toronto-headquartered financial technology company serving over four million Canadians, is hiring a Senior Data Scientist to join its Finance, Brokerage and Market Risk Data Science team. The group produces financial metrics and advanced analytics that inform financial planning, treasury and liquidity operations, and brokerage risk assessment for products such as margin trading and options. With the team's foundations in place, this role focuses on scaling analytics and reporting capabilities as the product suite grows more complex. The position suits someone who combines analytics engineering depth with enough financial and market-risk fluency to work credibly alongside brokerage, finance, and product partners. Wealthsimple operates as a hybrid team of more than 1,500 people across North America and offers health benefits, employer-matched group savings, 20 vacation days, wellness days, and a program allowing up to 90 days of work outside Canada per year for eligible roles.
Key responsibilities
- Own the development and upkeep of finance and market risk data marts, tuning them for performance, quality, reliability, and efficiency
- Design, build, and document data pipelines that produce key financial reports and metrics for stakeholders across the company
- Build, automate, and maintain brokerage reporting and monitoring systems with strong data integrity controls
- Partner with brokerage and market risk stakeholders to launch new financial products and support model development work
- Create dashboards and visualizations covering brokerage KPIs, profitability measures, and regulatory reporting needs
- Provide business intelligence support for trade and collateral monitoring, financial reporting, product performance analysis, and forecasting
- Convert complex business requirements into scalable analytics solutions
- Take part in code reviews and help shape best practices for data engineering and analytics development
- Mentor junior colleagues and share technical knowledge across the team
Key requirements
- 5+ years in data engineering or analytics development, including hands-on data mart architecture, design, and management
- Strong SQL skills: complex queries, performance tuning, and large-scale datasets
- Experience in brokerage operations or financial services with accounting and market risk knowledge (preferred)
- Familiarity with regulatory reporting requirements and financial product structures (an asset)
- Hands-on pipeline building and orchestration using dbt, Airflow, or comparable workflow tools
- Working knowledge of cloud infrastructure, particularly AWS (S3, Redshift, Snowflake, or equivalents)
- Python proficiency for data manipulation, automation, and scripting
- Version control experience with Git and GitHub, including branching, pull requests, and reviews
- Proven record translating business requirements into scalable, data-driven solutions
- Data visualization skills with Tableau, Looker, Power BI, or similar
- Grasp of analytics engineering principles for maintainable, well-documented data models
- Strong communication skills and comfort explaining technical concepts to non-technical audiences
- Seniority: Senior
- Work mode: Hybrid
- Key skills: SQL, Python, dbt, Airflow, AWS, Redshift, Snowflake, Git, GitHub, Tableau, Looker, Power BI, Data modeling, Data pipeline orchestration, Market risk analytics
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