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Senior Product Data Scientist
WealthsimpleUKRemotefull_timeVerifiedPosted 5 Nov 2025
About the role
Your career is an investment that grows over time!
Wealthsimple is on a mission to help everyone achieve financial freedom by reimagining what it means to manage your money. Using smart technology, we take financial services that are often confusing, opaque and expensive and make them transparent and low-cost for everyone. We’re the largest fintech company in Canada, with over 3+ million users who trust us with more than $100 billion in assets.
Our teams ship often and make an impact with groundbreaking ideas. We're looking for talented people who keep it simple and value collaboration and humility as we continue to create inclusive and high-performing teams where people can be inspired to do their best work.
The Data Science & Engineering (DSE) team is responsible for enabling data-driven decision making and building data products at Wealthsimple. They own building and maintaining a high-quality data warehouse, leveraging machine learning for smarter financial products, and using decision science to understand business decisions' cause and effect.
About the role:
Wealthsimple's SDI team is the driving force behind Self Directed Investing and Crypto products. The team is growing and we are seeking two Senior Data Scientists to lead high priority initiatives, take ownership as decision science experts, and ensure product strategy is grounded in data and analytics. This role will function as a product shaper, partnering directly with teams to frame critical business questions, design sophisticated measurement and experimentation strategies, execute causal analyses, and use compelling evidence to influence product roadmaps and fuel the growth of our SDI and Crypto products.
What this role is / isn’t:
Is: product decision science; roadmap influence; causality/experimentation; metrics strategy; opportunity sizing.
Isn’t: Not a data/ML engineering role. While you will build data pipelines and occasional models, your primary output is high-quality business decisions (engineering as a means, not the mandate.)
We’re a remote-first team, with over 1,000 employees coast to coast in North America. Be a part of our Canadian success story and help shape the financial future of millions — join us!
Read our Culture Manual and learn more about how w
Wealthsimple is on a mission to help everyone achieve financial freedom by reimagining what it means to manage your money. Using smart technology, we take financial services that are often confusing, opaque and expensive and make them transparent and low-cost for everyone. We’re the largest fintech company in Canada, with over 3+ million users who trust us with more than $100 billion in assets.
Our teams ship often and make an impact with groundbreaking ideas. We're looking for talented people who keep it simple and value collaboration and humility as we continue to create inclusive and high-performing teams where people can be inspired to do their best work.
The Data Science & Engineering (DSE) team is responsible for enabling data-driven decision making and building data products at Wealthsimple. They own building and maintaining a high-quality data warehouse, leveraging machine learning for smarter financial products, and using decision science to understand business decisions' cause and effect.
About the role:
Wealthsimple's SDI team is the driving force behind Self Directed Investing and Crypto products. The team is growing and we are seeking two Senior Data Scientists to lead high priority initiatives, take ownership as decision science experts, and ensure product strategy is grounded in data and analytics. This role will function as a product shaper, partnering directly with teams to frame critical business questions, design sophisticated measurement and experimentation strategies, execute causal analyses, and use compelling evidence to influence product roadmaps and fuel the growth of our SDI and Crypto products.
What this role is / isn’t:
Is: product decision science; roadmap influence; causality/experimentation; metrics strategy; opportunity sizing.
Isn’t: Not a data/ML engineering role. While you will build data pipelines and occasional models, your primary output is high-quality business decisions (engineering as a means, not the mandate.)
In this role, you will have the opportunity to:
- Influence strategy. Define north-star/guardrails and the measurement plan for your domain; surface the trade-offs that drive roadmap decisions.
- Originate insights. Proactively uncover opportunities and risks; size the upside with clear assumptions and ranges; recommend what to do next.
- Drive experimentation & causality. Design ABs/quasi-experiments, ensure power/validity, and translate results into go/no-go and scope decisions.
- Partner with senior leadership. Work with Director/VP Product, Eng, and GM to prioritize bets, set targets, and review performance.
- Raise leverage with data products. Specify the semantic layer / core marts your area needs; collaborate with Analytics Engineering to build durable foundations.
- Tell the story. Create crisp, exec-ready narratives and dashboards that let leaders decide in one meeting.
You’ll be successful if you have:
- 6–10+ years in product analytics/decision science (or equivalent), including time as the primary DS for a product area with business outcomes to show.
- A portfolio of self-initiated work that changed roadmaps or targets.
- Depth in experimentation & causal inference; identify opportunities for experimentation and design the experiment that will best inform the business.
- Executive-caliber communication: concise narratives, sharp trade-off framing, and clear recommendations.
- Strong SQL and Python; you write reliable analysis code and collaborate well with Analytics Engineering/Platform teams (dbt familiarity is a plus).
We’re a remote-first team, with over 1,000 employees coast to coast in North America. Be a part of our Canadian success story and help shape the financial future of millions — join us!
Read our Culture Manual and learn more about how w
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