About this role
Build something people loveWealthsimple'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.
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About the roleThe Staff Data Scientist role is part of the Sales Data Science team at Wealthsimple, which focuses on building data products that make the conversion process as easy as possible for our clients, and enable our sales and CXO teams to target, and offer the right products/offerings to client leads to drive conversions.
This individual will leverage deep expertise in operations analytics and modeling, working across large, complex structured and unstructured datasets to identify opportunities to make the account transfer experience simpler, faster, and more reliable for clients, as well as more efficient for our Transfers Operations and Customer Support teams.You will partner closely with stakeholders across Product, CXO, Operations, and Data to build scalable data products and analytical frameworks that uncover systemic operational failures and root causes, surface high-impact improvement opportunities, and enable proactive, data-driven client engagement and interventions.
As a Staff Data Scientist on the team, you will play a key leadership role in defining the analytical and modeling strategy for transfers. You will lead complex investigations, build scalable data products, and partner with senior stakeholders to turn insights into durable improvements in client experience, operational efficiency, and retention. This role offers the opportunity to own a critical business domain end-to-end and drive meaningful impact at scale, as well as be a technical leader on the data science team.
What you'll doOwn the end-to-end analytical and modeling strategy for Account Transfers, operating with high autonomy in a complex, ambiguous problem space with material client and business impact.
Execute deep investigations across large, complex structured and unstructured datasets to uncover systemic operational failures, root causes, and improvement opportunities within the transfers ecosystem.
Design and build scalable data models and analytical frameworks that enable proactive identification of transfer failures, early risk detection for at-risk client transfers and actionable signals for CXO and Product teams.
Apply advanced modeling techniques (e.g., clustering, segmentation, predictive modeling, causal analysis) to identify distinct transfer behaviour archetypes, surface institutional-level patterns across external counterparties, and inform differentiated operational and product strategies.
Partner closely with Product, CX, Operations, and Engineering leaders to translate analytical insights into product roadmap decisions, operational process design, and client-facing interventions that measurably improve outcomes.
Build and productionize data products (ML models, dashboards, decision tools) that embed analytics directly into workflows and decision-making.
Measure and communicate impact, tying analytical work to improvements in transfer success rates, client experience, operational efficiency, and retention.
Act as a technical and analytical leader by:
Defining best practices for modeling, experimentation, and measurement in the transfers domain.
Mentoring senior data scientists and raising the bar for analytical rigor.
Influencing data strategy beyond immediate team boundaries.
Skills you bring7–10+ years of experience in data science, applied statistics, analytics, machine learning, or operations research and at least 3-5 years in Senior or Staff-level roles.
Strong background working with complex, multi-step operational systems (e.g., operations, payments, transfers, risk, fraud, compliance, customer lifecycle, or similar domains).
Experience applying operations research techniques such as optimization, simulation, queuing theory, or decision modeling to improve operational outcomes.
Deep expertise in statistical analysis, experimentation, and inference on real-world dataHands-on experience building predictive and prescriptive models (e.g., classification, regression, anomaly detection, routing).
Expert SQL skills, including complex joins, window functions, and performance optimization.
Excellent Python skills for data analysis, modeling, optimization, and production-ready workflows.
Experience working with large, messy, and incomplete datasets, including both structured and unstructured data.
Excellent communication skills, with experience presenting complex analytical or optimization results to non-technical stakeholders and influencing product strategy, operational decisions or roadmap priorities.
Track record of driving measurable business or client impact through data science and/or operations research work.
Experience mentoring or coaching senior data scientists and raising analytical standards within a team.
Comfortable operating with high autonomy and making judgment calls under uncertainty.
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 health days per year
✈️ 90 days away: work outside Canada for up to 90 days per year
👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS
🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.
ICYMITechnology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.
Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.
Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.
AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.