Senior Data Scientist - Commercial Banking Data & Analytics, Toronto

Scotiabank; Toronto; On-site; CAD 120,000 - 160,000; Full time

Job summary

Scotiabank in Toronto is seeking a Senior Data Scientist to advance Commercial Banking Data & Analytics platforms, leveraging enterprise datasets, predictive models, and AI technologies to drive business decisions. You will collaborate with Analytics, Credit Risk, Data, and Technology teams to modernize platforms, monitor models, and ensure governance and reproducibility across production environments.

Strong Python and SQL skills, and production analytics experience are essential for success in

Qualifications

• University degree in a quantitative field (CS/Engineering/Math/Stats/Economics).
• Significant hands-on experience in data science, machine learning, or advanced analytics.
• Advanced proficiency in Python and SQL.
• Experience supporting production-level analytical or predictive modelling solutions.
• Experience with model governance, documentation, controls, validation, or model risk management.
• Experience with cloud-based analytics tools (Azure Databricks, GCP, BigQuery) is a plus.

Responsibilities

• Support operation, maintenance, and enhancement of an enterprise analytics and predictive modeling platform.
• Monitor, assess, and improve model performance including recalibration and validation support.
• Investigate data quality, model output, and production issues via root-cause analysis.
• Develop understanding of data lineage, feature engineering, and source-system dependencies.
• Collaborate with cross-functional teams to deliver platform enhancements and production support.
• Contribute to platform modernization and streamline legacy analytics processes.
• Support governance, documentation, controls, and model risk management.

Skills

Data Science

Predictive Modeling

Machine Learning

Python

SQL

Model monitoring

Stakeholder management

Production data pipelines

Education

University degree in quantitative field

Tools

Azure Databricks

Google Cloud Platform

BigQuery

Job description

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Title: Senior Data Scientist - Commercial Banking Data & Analytics, Toronto

Requisition ID: 275108

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

About the Opportunity:

We are seeking a highly analytical and technically skilled Senior Data Scientist to join our Commercial Banking Data & Analytics team. In this role, you will help support, enhance, and modernize a critical predictive modeling and analytics platform used by Commercial Banking and Risk partners across the organization.

Working closely with the Lead Data Scientist, you will play a key role in ensuring the stability, integrity, and evolution of business-critical analytical capabilities. This is an opportunity to work with complex data ecosystems, advanced predictive models, enterprise-scale datasets, and emerging AI technologies while partnering with stakeholders across Analytics, Credit, Risk, Data, and Technology teams.

If you thrive on solving complex problems, uncovering insights in large datasets, and strengthening analytical solutions that influence business decisions, we'd love to hear from you.

How You Will Make an Impact:

• Support the operation, maintenance, and enhancement of a critical enterprise analytics and predictive modeling platform
• Monitor, assess, and improve model performance, including recalibration, validation support, and methodology enhancements
• Investigate and resolve complex data quality, model output, and production issues through structured root-cause analysis
• Develop a deep understanding of data lineage, feature engineering, business rules, and source-system dependencies
• Collaborate with Commercial Banking, Credit Risk, Data, and Technology teams to deliver platform enhancements and support production operations
• Contribute to platform modernization initiatives and help identify opportunities to streamline legacy analytical processes
• Support governance, documentation, controls, and model risk management activities
• Establish and promote best practices in model development, testing, monitoring, deployment, and reproducibility
• Serve as a key partner and backup to the Lead Data Scientist, ensuring continuity of critical analytical capabilities
• Explore opportunities to leverage advanced analytics, Generative AI, and emerging AI technologies to create business value

What You Will Bring to the Team:

• Extensive experience in Data Science, Predictive Modeling, Machine Learning, or a related quantitative field
• Proven experience supporting complex analytics platforms, predictive models, or enterprise data solutions in production environments
• Strong expertise in statistical modeling, model monitoring, performance evaluation, validation support, and model interpretation
• Advanced Python and SQL skills, with experience performing large-scale data analysis, feature engineering, and production support
• Experience working with enterprise datasets, data quality management, lineage analysis, and data transformation processes
• Strong understanding of machine learning operations, production data pipelines, testing frameworks, version control, and deployment practices
• Excellent problem-solving skills with the ability to work through ambiguity and independently investigate complex technical issues
• Strong communication and stakeholder management skills, with the ability to translate technical concepts into business insights
• A collaborative mindset and demonstrated ability to work across multidisciplinary teams

Must-Have:

• University degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related quantitative discipline
• Significant hands-on experience in data science, machine learning, or advanced analytics
• Advanced proficiency in Python and SQL
• Experience supporting production-level analytical or predictive modeling solutions
• Experience with model governance, documentation, controls, validation, or model risk management practices
• Strong understanding of enterprise data environments and analytical workflows

Nice-to-Have:

• Experience with Azure Databricks, Google Cloud Platform (GCP), and BigQuery
• Experience within Financial Services, Commercial Banking, Credit Risk, Portfolio Management, or Early Warning Analytics
• Exposure to Generative AI, Large Language Models (LLMs), agentic workflows, or AI-assisted development
• Experience working within regulated environments.

What's In It for You:

• Opportunity to support and influence business-critical analytics used by Commercial Banking and Risk leaders
• Exposure to complex enterprise datasets, predictive models, and advanced analytical environments
• Collaborative work with senior stakeholders across Analytics, Credit, Risk, Data, and Technology teams
• Opportunity to contribute to platform modernization and emerging AI initiatives
• A challenging and rewarding environment that values innovation, analytical rigor, and continuous learning

We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.

Location(s): Canada : Ontario : Toronto

Scotiabank 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.

We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.