Business Insights Specialist ( Data Quality & Validation Financial Crimes

Work Location:

Toronto, Ontario, Canada

Hours:

0 Line of Business:
Analytics, Insights, & Artificial Intelligence Pay Details: $96,900 - $136,800 CAD TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role.

The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs. As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

The Business Insights Specialist, Data Quality & Validation is an individual contributor responsible for the design, execution, validation, and ongoing monitoring of data quality controls supporting business rules, analytical models, and regulatory / management reporting. This role serves as a subject matter expert (SME) in data, focusing on data quality and partnering closely with business, analytics, technology, and governance stakeholders to ensure data is accurate, complete, consistent, timely, and fit for purpose across the end-to-end data lifecycle.

The role operates without direct people management responsibilities but carries enterprise-level accountability, influence, and decision authority over data quality standards, validation approaches, and issue remediation outcomes.

• Design, implement, and maintain automated and manual data quality rules to validate critical data elements used in models, dashboards, and regulatory or executive reporting.
• Define validation logic for accuracy, completeness, uniqueness, validity, consistency, and timeliness aligned to enterprise data standards.
• Partner with data engineering and analytics teams to embed data quality controls across data capture, data at rest, data movement, and data usage layers.
• Model & Analytics Data Validation
  • Perform independent validation of data inputs, transformations, and outputs supporting analytical and detection models.
  • Assess data quality risks impacting model performance, explainability, and downstream decision-making.
  • Establish ongoing monitoring metrics and thresholds to detect data drift, anomalies, and control breaks affecting models and analytics.
• Reporting & Downstream Data Assurance
  • Validate datasets used for regulatory, risk, finance, and management reporting, ensuring reported figures reconcile to authoritative sources.
  • Support reporting owners by identifying data quality gaps, root causes, and remediation actions prior to publication.
  • Provide data quality attestations, summaries, and insights to governance forums as required.
• Monitoring, Metrics & Issue Management
  • Develop and maintain data quality dashboards and KPIs that track rule performance, exceptions, and trends over time.
  • Lead investigation of data quality issues, document findings, and drive remediation plans in partnership with data owners and custodians.
  • Ensure data quality issues are logged, tracked, and resolved in accordance with enterprise data concern and remediation processes.
• Governance, Standards & Advisory
  • Act as a trusted advisor to business and technology teams on Enterprise Data Management Standard published by EDMO.
  • Contribute to the evolution of enterprise data risk frameworks, policies, and best practices.
  • Support audits, regulatory inquiries, and internal reviews by providing evidence of data quality controls and monitoring effectiveness.

• Experienc…