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Scotiabank

Senior Data Scientist - Commercial Banking Data & Analytics, Toronto

Toronto, ON, M5H 1H1, Canada

Posting language: English
Posted: Sep 29, 2026

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Original job description

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:

As a Senior Data Scientist, you will:

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:

Master's degree in a quantitative discipline
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

Ready to Apply?

If you're passionate about leveraging data, predictive modeling, and AI to solve complex business challenges while driving meaningful impact, we encourage you to apply and join our Commercial Banking Data & Analytics team.

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. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. 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.

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More about this job

Responsibilities

The Senior Data Scientist will support, enhance, and modernize critical predictive modeling and analytics platforms for Commercial Banking and Risk teams. They will also monitor model performance, resolve production issues, and collaborate with cross-functional teams to deliver analytical solutions.

Requirements

Candidates must have a university degree in a quantitative discipline and significant hands-on experience in data science or machine learning. Advanced proficiency in Python and SQL, along with experience in model governance and production-level analytical environments, is required.

Skills

Python
SQL
Predictive modeling
Machine learning
Data science
Statistical modeling
Model monitoring
Model governance
Feature engineering
Data lineage
Production support
Risk management
Data quality management
Stakeholder management
Generative AI
Azure Databricks

Benefits

Inclusive culture
High-performing environment
Professional development
Continuous learning

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Predictive Modeling
Machine Learning
Python
SQL
Commercial Banking
Credit Risk
Model Governance
Azure Databricks
Google Cloud Platform
BigQuery
Generative AI
Large Language Models
Data Lineage
Feature Engineering
Model Monitoring
Risk Management
Analytics
Production Support
Data Transformation
Portfolio Management
Early Warning Analytics
AI-assisted development
Root-cause analysis
Enterprise datasets

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