Business Intelligence and Reporting Analyst (Toronto)

Business Intelligence and Reporting Analyst (Toronto)

06 Nov
|
TD
|
Toronto

06 Nov

TD

Toronto

Line Of Business

Analytics, Insights, & Artificial Intelligence

Work Location

Toronto, Ontario, Canada

Hours

35

Line Of Business

Analytics, Insights, & Artificial Intelligence

Pay Details

$66,800 - $94,300 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 at TD. Our 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

CUSTOMER

- Produce reporting packages, dashboards, scorecards and analytical outputs for business partners, with focus on understanding objectives and supporting business decision making.
- Use established methodologies to generate interactive visualizations, analytical outputs and data solutions in a fast-paced, high-volume ad-hoc reporting environment.
- Lead or contribute to strategic initiatives involving complex analytical investigations, monitoring solutions, process improvements and scalable data products.
- Own or coordinate assigned analytics work from intake through delivery, including planning, task breakdown, timelines, dependencies and progress updates.
- Conduct analysis to provide business intelligence that supports management and business partner decisions,



including trend identification and interpretation of datasets.
- Create BI reporting packages and dashboards using enterprise data infrastructure, DataMarts and other approved data sources, translating findings into explicit and meaningful insights.
- Validate the quality and integrity of data through validation, reconciliation and analysis, escalating issues as required.
- Develop meaningful insights highlighting trends, anomalies and business implications.
- Work with business partners to understand objectives, clarify requirements and translate them into analytical and data solution requirements.
- Conduct root-cause and impact analysis of operational or risk-related issues by connecting information across datasets, systems and business processes.
- Analyze historical patterns and contributing factors to identify recurring themes and opportunities for earlier detection or prevention.
- Contribute to the design, testing and refinement of business rules, indicators or monitoring solutions, including back-testing and exception analysis.
- Support investigation and resolution of data issues through analysis, impact assessment and collaboration with technical or data partners as needed.
- Operate effectively in situations with some ambiguity by applying analytical thinking,



clarifying assumptions and developing structured recommendations.
- Identify and contribute to opportunities to automate, streamline and leverage AI-enabled solutions to improve efficiency and scalability.
- Manage multiple priorities and deliver high-quality outputs within agreed timelines while maintaining data integrity and clear stakeholder communication.

SHAREHOLDER

- Adhere to enterprise frameworks, governance and risk practices.
- Ensure compliance with applicable policies, regulatory and internal requirements.
- Conduct analysis that supports business decisions and operational effectiveness.
- Monitor productivity and support improvements to turnaround time in a high-volume ad-hoc environment.
- Support remediation activities related to data quality or reporting issues.
- Build and maintain effective working relationships across business and analytics teams.
- Promote data governance, documentation and operational discipline in day-to-day work.
- Apply structured quality-control practices, including peer review, reconciliation, exception analysis and documented validation evidence.
- Maintain reusable and reproducible analytical processes with clear documentation of code, data sources, business rules, assumptions and limitations.

EMPLOYEE / TEAM

- Contribute as a strong team member by supporting collaboration, knowledge sharing and continuous improvement.
- Apply sound BI and analytics practices and share practical recommendations with peers.
- Stay current with relevant trends including automation, AI and advanced analytics.
- Support onboarding, mentoring and knowledge sharing where appropriate.
- Co

📌 Business Intelligence and Reporting Analyst (Toronto)
🏢 TD
📍 Toronto

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