Work Location:
Toronto, Ontario, Canada

Hours:
37.5

Line of Business:
Analytics, Insights, & Artificial Intelligence

Pay Details:
$96,900 - $136,800 CAD

This role is eligible for a discretionary variable compensation award that considers business and individual performance.

Job Description:
Department Overview

The Enterprise Stress Testing group manages the Bank's enterprise and regulatory stress testing programs, ad hoc stress analysis and support for climate stress analysis. The group coordinates scenario execution, balance sheet and income statement projections, aggregation of results, and reporting to senior management, Board committees and regulators. The Aggregation & Control team is responsible for combining outputs from multiple workstreams and producing complete, accurate, controlled and traceable enterprise stress testing results.

Role Overview

The Manager, Stress Testing Data, Controls & Analytics is a senior hands-on delivery role within Aggregation & Control. The role combines stress testing subject-matter expertise, data management, technical analysis, control design, regulatory reporting and cross-functional delivery. The successful candidate will sustain current MST and EWST execution while helping modernize the operating model for MST 2.0 using Python, Databricks and Power BI.

This role requires a professional who can move confidently between business requirements, regulatory templates, data mappings, transformation logic, controls, reconciliations and executive-ready reporting. The individual must be able to challenge results, investigate issues to root cause, translate requirements for technology partners and maintain audit-ready evidence of key decisions and approvals.

Key Accountabilities
1. Stress Testing Execution and Regulatory Reporting
• Lead or coordinate the aggregation, validation and submission of MST, EWST and related regulatory stress testing results, including templates, supporting schedules and management reporting outputs.
• Interpret regulatory template requirements and translate them into clear data, mapping, ownership, control and reporting requirements for business segments and technology partners.
• Coordinate cycle activities across workstreams, monitor data readiness and issue resolution, and provide clear status, risks and decisions to senior stakeholders.
• Perform detailed review and challenge of results, including actuals, projections, ratios, adjustments, eliminations, scenario and version comparisons, and movement analysis.
• Maintain complete and audit-ready support for submissions, including approvals, attestations, reconciliations, control evidence, issue logs and change records.

2. Data Aggregation, Mapping and Governance
• Own and maintain critical mapping and reference data used to connect source data, regulatory codes, management reporting line items, model outputs, schedules and enterprise reporting views.
• Design and govern data quality rules, lineage, ownership dictionaries, metadata and reconciliation points across the end-to-end aggregation process.
• Partner with Finance, business segments, reporting teams and technology to improve access to source data, reduce manual data handling and establish reusable governed datasets.
• Support the design and implementation of stress testing data marts, semantic models and scalable data structures that provide a controlled single source for reporting and analysis.
• Assess downstream impacts of source, methodology, template and configuration changes and ensure changes are appropriately tested, approved and documented.

3. Controls, Reconciliation and Assurance
• Design, execute and enhance preventative and detective controls for completeness, accuracy, reasonability, mapping integrity, version consistency, actuals-to-projection continuity, ratios and consolidation eliminations.
• Investigate data and reporting exceptions, determine root cause, quantify impact, coordinate remediation and document conclusions for management and audit review.
• Establish repeatable testing, peer review and sign-off practices for configuration files, data transformations, dashboards, reports and automation solutions.
• Monitor controls performed by technology teams and dependent workstreams, challenge unresolved exceptions and confirm evidence is sufficient for regulatory and internal assurance expectations.
• Identify opportunities to automate reconciliations, exception reporting, attestation workflows and evidence capture.

4. MLE 2.0 and Analytics Modernization
• Act as a business and data lead for the transition from SAS and Excel-intensive processes toward Python and Databricks-based data pipelines, controls and analytics.
• Translate current business logic, mappings and controls into well-defined requirements, acceptance criteria and test cases for MST 2.0 and MLE 2.0.
• Use Python, SQL and Databricks notebooks to profile data, validate transformations, reconcile outputs, automate repeatable analysis and support production readiness.
• Design or oversee Power BI semantic models, measures, dashboards and reporting products that support controlled self-service analysis and consistent enterprise reporting.
• Ensure modernized solutions include versioning, lineage, role-based access, change control, testing, monitoring, documentation and support procedures from inception.
• Support parallel-run testing and back-testing between current and target-state solutions, with clear documentation of variances, defects and resolution.

5. Process Improvement and Change Delivery
• Lead initiatives to automate manual actuals population, projections, adjustments, ratio checks, management and regulatory reconciliations, and recurring reporting outputs.
• Develop process maps, business requirements, control requirements, implementation plans, test strategies, standard operating procedures and training materials.
• Prioritize enhancements based on regulatory risk, control effectiveness, cycle efficiency, scalability and stakeholder value.
• Coordinate delivery across business, data, technology and reporting teams and ensure solutions are operationally supportable after implementation.
• Promote reusable design patterns, disciplined documentation and continuous improvement across the Aggregation & Control function.

6. Stakeholder Leadership
• Build strong working relationships across Enterprise Stress Testing, Finance, Treasury, business segments, Data, Technology, Risk and regulatory reporting teams.
• Communicate complex data, financial and technical issues clearly to audiences with varied levels of seniority and technical expertise.
• Facilitate working groups, requirements discussions, issue-resolution sessions and decision forums, and drive actions to completion.
• Provide technical and process guidance to team members and project resources and support knowledge transfer for critical processes.

Required Qualifications and Experience
• University degree in Finance, Accounting, Economics, Mathematics, Statistics, Computer Science, Data Engineering, or another relevant quantitative discipline.
• Five or more years of progressive experience in stress testing, regulatory reporting, treasury, finance data, risk data, advanced analytics, data engineering or a related field.
• Demonstrated experience working with large financial datasets, complex mappings, transformation logic, reconciliations and controlled reporting processes.
• Experience translating business and regulatory requirements into data specifications, controls, test cases and implementation deliverables.
• Advanced SQL skills and practical programming experience in Python for data manipulation, validation, automation and testing.
• Hands-on experience with Databricks or a comparable cloud analytics platform, including notebooks, data pipelines, data quality checks and version-controlled development practices.
• Advanced Power BI experience, including data modelling, semantic models, DAX, report development, refresh processes, security concepts and performance considerations.
• Working knowledge of SAS and Excel sufficient to understand, validate and transition existing stress testing processes and end-user computing solutions.
• Strong understanding of data governance, lineage, metadata, change management, control design and audit evidence requirements.
• Excellent written and verbal communication, stakeholder management, problem solving and project delivery skills.

Preferred Qualifications and Experience
• Knowledge of enterprise stress testing, MST, EWST, OSFI regulatory templates, capital, liquidity, balance sheet and income statement concepts.
• Experience with MLE, M4, P3, BCAR, Hyperion/FCCS, regulatory reporting data or comparable financial reporting infrastructure.
• Experience designing star schemas, governed semantic layers, reusable reporting datasets or data marts for financial reporting.
• Experience with Azure data services, ADLS, Git or Azure DevOps, CI/CD practices, automated testing and production support controls.
• Experience leading cross-functional initiatives and supporting implementation through requirements, design, testing, deployment and stabilization.
• CPA, CFA, FRM, MBA, PMP, data engineering, cloud or analytics certification is an asset.

Core Competencies and Personal Qualities
• Deep analytical curiosity and strong attention to detail
• Controls mindset and professional skepticism
• Ability to connect business, financial and technical concepts
• Sound judgement under tight regulatory timelines
• Structured problem solving and root-cause analysis
• Clear executive and technical communication
• Strong relationship management and ability to influence
• Ownership, initiative and follow-through
• Comfort operating through ambiguity and change
• Commitment to documentation, knowledge transfer and sustainable solutions

Work activities include a blend of highly collaborative activities and individual deliverables. Individuals are expected to be onsite 4 days a week. Colleagues may spend more or less days in office as required by the business line.