Title: Lead Data Scientist, Canadian Commercial BankingRequisition ID: 271520Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.About the Opportunity:As a Lead Data Scientist within Commercial Banking Data and Analytics at Scotiabank, you will play a critical role in the stewardship, stability, enhancement, and ongoing operation of a business-critical analytics and predictive modeling platform supporting Commercial Banking and Risk stakeholders.In this role, you will provide technical leadership across complex data assets, predictive models, business rules, and production processes. You will work through ambiguity, reverse engineer existing methodologies and code, assess data and model risks, and partner across Analytics, Credit, Risk, Data, and Technology teams to strengthen analytical capabilities that help enable sound business decisions.How You Will Make an Impact:Assume technical ownership of a critical enterprise analytics platform, including its predictive models, methodologies, data assets, business rules, code base, and production processesRapidly acquire platform knowledge and independently determine how complex, interconnected components operate, including areas with limited documentation or institutional knowledgeLead platform stabilization by identifying key data, model, process, and operational risks; prioritizing remediation; and establishing a sustainable support modelOwn model stewardship, including performance monitoring, methodology assessment, recalibration, enhancements, controls, and support for governance and validation activitiesInvestigate and resolve complex data quality, model output, pipeline, and production issues through structured root cause analysisDevelop a detailed understanding of data lineage, transformations, feature logic, source-system dependencies, and downstream uses; ensure that material changes are assessed and documentedMaintain clear documentation of data sources, model methodologies, code, controls, operating procedures, issue resolution, and key business rulesPartner with Commercial Banking, Credit, Risk, Data, and Technology stakeholders to ensure the platform remains reliable and fit for purposeProvide technical direction across the cross-functional resources supporting the platform, with transparent accountability across data, modeling, credit, and operational activitiesEstablish repeatable development, testing, release, monitoring, and incident-management practices that strengthen resiliency and reduce key-person dependencyIdentify opportunities to simplify and modernize legacy analytical processes and, as capacity allows,



contribute to broader advanced analytics and AI initiativesMentor data scientists and analysts and promote high standards for analytical rigor, documentation, reproducibility, and responsible model useWhat You Will Bring:Extensive experience in data science, predictive modeling, advanced analytics, or a related quantitative discipline, including accountability for production analytical assetsProven experience assuming ownership of a complex analytical platform, predictive model, or enterprise data asset and successfully stabilizing and operationalizing itDemonstrated ability to rapidly understand complex or partially documented business processes, data structures, model methodologies, code bases, and system dependenciesDeep expertise in statistical modeling and machine learning, including model performance assessment, monitoring, recalibration, feature evaluation, validation support, and interpretationStrong experience with large-scale, multi-source enterprise datasets, including data lineage, quality investigation, transformation logic, and reproducible analysisAdvanced Python and SQL skills for data investigation, feature engineering, model development, testing, and production support; GCP and BigQuery experience is preferredStrong understanding of production data and ML pipelines, orchestration, version control, testing, deployment practices, and collaboration with data engineering and technology teamsExperience with model governance, model risk management, documentation, controls, and audit or validation support in a regulated environmentStrong structured problem-solving skills and sound judgment when working through ambiguous, high-impact technical or business issuesExcellent communication skills, including the ability to explain complex data and model concepts to senior business, Risk, Credit, and technical stakeholdersDemonstrated ability to provide technical leadership, influence cross-functional teams, and mentor data professionals without formal reporting authorityExperience in financial services, commercial banking, credit risk, portfolio management, or early warning analytics is strongly preferredExperience applying GenAI, large language models, agentic workflows, or AI-assisted development is an asset,



but secondary to deep data and modeling experienceNice-to-have:Experience in financial services, commercial banking, credit risk, portfolio management, or early warning analyticsExperience with GCP, BigQuery, or similar cloud-based data platformsExperience applying GenAI, large language models, agentic workflows, or AI-assisted developmentFamiliarity with credit, risk, or commercial banking data ecosystems and related business processesEducation:University degree in a relevant quantitative discipline such as Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field. A Master's degree or PhD is preferred.What's in it for You?When you join the bank, you are not just taking a job, you are becoming part of a culture that values inclusion, accountability, integrity, and client-centricity — that is our ScotiaBond, the foundation for how we support our people and deliver for our clients.A competitive Total Rewards package including performance-based bonus and flexible benefitsOngoing career development and coaching from experienced leaders, with opportunities to grow within Commercial Banking, analytics, technology, and across ScotiabankThe opportunity to lead meaningful work on business-critical analytics and predictive modeling platforms that support Commercial Banking and Risk decision-makingA dynamic, collaborative, and high-performing team that values partnership, inclusion, analytical rigor, and shared successExposure to complex data ecosystems, advanced analytics, model governance, and cross-functional business challenges that will accelerate your learning and impactWorking Conditions:Work in a standard office-based environment; Additional hours may occasionally be required to support critical production issues, releases, or business priorities.Location(s): Canada : Ontario : TorontoScotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know.

📌 Lead Data Scientist, Canadian Commercial Banking (Toronto)
🏢 Scotiabank
📍 Toronto