Sr Data Scientist, AI Products
WFA Digital Insight
Wealthsimple’s AI Products Data Science team sits at the crossroads of research and product, giving a senior data scientist a rare chance to turn cutting‑edge models into everyday financial tools for millions. The role isn’t just about building transformers; it demands a product‑first mindset—defining KPIs, running causal experiments, and iterating based on real user feedback. Collaboration is baked in, with daily partnership across product managers, designers, and engineers, meaning communication skills are as vital as technical depth. Candidates should be comfortable with LLM fine‑tuning, production pipelines, and translating model performance into clear business impact before they even ship the code.
Job Description
BUILD SOMETHING PEOPLE LOVE Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. 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. The AI Products Data Science team is a full-stack, product-driven unit at the heart of Wealthsimple’s innovation. We own the end-to-end AI lifecycle: from model architecture and data pipelines to designing experiments that drive real-world impact for over 4 million Canadians. We are looking for a Senior Data Scientist who thrives at the intersection of AI research and product development. You are someone who can design and scale complex models while maintaining a product manager’s mindset, constantly asking how our technology creates value for our clients. In this collaborative role, you will transform technical breakthroughs into seamless product experiences, ensuring that every model we ship moves the needle for our business. In this role, you'll have the opportunity to: - Lead the full AI product lifecycle: from identifying user pain points and defining KPIs to training foundation models and measuring real-world impact.
- Design and execute rigorous experiments (A/B tests, causal inference) to validate new AI features and drive product optimizations.
- Partner with Product Managers, Designers, and Engineers to translate business goals into a technical AI roadmap, ensuring our model development stays aligned with user needs and technical feasibility.
- Build and maintain production-grade training pipelines and evaluation harnesses using reproducible, well-tested code.
- Analyze production feedback and user interactions to iteratively refine models and maximize value.
- Foster a collaborative culture: mentor teammates, simplify complex problems, and drive iterative, high-impact delivery.
What you Bring
- Deep product sense: define success metrics, translate vague business objectives into measurable hypotheses, and measure product impact through A/B testing and causal inference.
- Experience with product analytics to derive actionable insights that inform product roadmaps.
- Proven track record of converting model outputs into business outcomes; comfortable communicating technical findings to cross-functional partners (PMs, designers, engineers) to drive alignment.
- Experience designing, training, and shipping production AI models, with depth in transformer architectures and LLMs.
- Solid fundamentals (attention, tokenization, embeddings, regularization) and failure mode analysis.
- Familiarity with fine-tuning (LoRA, adapters), knowledge distillation, quantization, and instruction tuning.
How to Stand Out
- Highlight specific LLM fine‑tuning projects in your resume; include metrics on model performance and downstream impact.
- Prepare a short case study showing how you designed an A/B test for an AI feature and measured business outcomes.
- Practice explaining complex model concepts in plain language; interviewers will assess your ability to communicate with product and design partners.
- Showcase any open‑source contributions or publications; they demonstrate depth and community involvement.
- When discussing compensation, research typical equity and benefit packages for senior data scientists at Canadian fintech firms to negotiate confidently.
- Watch for red flags such as vague expectations around deliverables or lack of clear mentorship structures during the interview.
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