Staff Data Scientist

Join us to build a more rewarding financial future for all Canadians At Neo, we’re on a mission to build a more rewarding financial future for all Canadians. Life at a rapidly scaling tech startup isn’t for everyone. It’s complex, fast-paced, high-pressure, but also incredibly fulfilling. Since its founding in 2019, Neo has gained incredible traction and is one of the fastest-growing fintech companies in Canada. - #1 on Deloitte’s Technology Fast 50 for 2023, 2024, and 2025 https://www.newswire.ca/news-releases/neo-financial-achieves-first-ever-three-peat-win-as-number-one-on-deloitte-s-technology-fast-50-list-889692540.html — the first company ever to achieve a three-peat at the top! - #1 Fastest Growing Company in Canada for 2024 by Globe & Mail https://www.businesswire.com/news/home/20240927952651/en/Neo-Financial-Ranks-No.-1-on-The-Globe-and-Mail%E2%80%99s-2024-List-of-Canada%E2%80%99s-Top-Growing-Companies - Top-ranked mobile apps and credit cards - Team of 500+ people - 1M+ customers - 10K+ retail partners The Role We're looking for a Staff Data Scientist to lead technical strategy and execution across our data science function. In this role you will own end-to-end model development — from problem framing and feature engineering through to production validation and performance monitoring — across credit risk, fraud, and marketing. You'll mentor and develop a team of data scientists, shape the DS vision, and collaborate closely with business and executive stakeholders to identify and prioritize high-value opportunities. This is a high-impact, senior individual contributor role. You'll own model quality and outcomes end-to-end — ensuring the models we build are rigorous, trustworthy, and commercially impactful. Because we operate in a regulated financial services environment, that standard extends beyond predictive accuracy — models must be reproducible, auditable, and built with the governance rigour that regulators and internal risk functions require. We're looking for someone who brings deep technical range — spanning classical ML, neural approaches, and causal inference — alongside the leadership and communication skills to drive alignment across technical and business teams. On-site, Calgary, AB. WHAT YOU'LL DO - Lead technical strategy and end-to-end delivery of ML models across credit risk, fraud, and marketing — spanning both batch and real-time inference use cases - Develop and evaluate neural network architectures (e.g., embeddings, sequential models) as complements to tree-based models, improving prediction accuracy where tabular approaches have limits - Apply causal inference techniques to measure treatment effects, improve decision-making, and move beyond correlational models - Build models to enterprise-grade standards: modular, well-tested code; reproducible pipelines; thorough documentation; and governance artifacts (model cards, validation reports, audit trails) that meet the reliability and compliance requirements of a regulated financial services environment - Champion model explainability and business trust via SHAP insights and clear communication with senior stakeholders - Manage the technical development of data scientists — guide complex projects, lead code reviews, and drive knowledge sharing across the team - Collaborate with business and executive leaders to identify and prioritize high-value DS initiatives - Drive an AI-first way of working — leveraging AI coding tools (e.g. Cursor, Claude Code) heavily across the DS workflow, from exploration and feature engineering to code review and documentation, and driving adoption across the team WHAT YOU BRING REQUIRED - 10+ years deploying production ML, driving commercial outcomes, and leading technical teams - Background in credit risk, fraud detection, or marketing ML in financial services - Deep proficiency in Python (pandas, polars, scikit-learn) and SQL; hands-on experience with Snowflake and/or Databricks, and familiarity with dbt - Tree-based mo