Work Location:
Toronto, Ontario, Canada
Hours:
37.5
Line of Business:
Analytics, Insights, & Artificial Intelligence
Pay Details:
$81,600 - $115,200 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:
Department Overview
The Real Estate Secured Lending (RESL) Business Intelligence team within Risk (CLA&BI - Credit Loss Allowance & Business Intelligence) is responsible for delivering data, analytics, and insights that support the modernization, monitoring, and optimization of RESL risk reporting.
The team partners closely with RESL 2A, Policy, and Technology teams to enable end-to-end visibility into risk performance metrics, strengthen governance, and drive data-informed decision-making. This is achieved through the development of scalable data pipelines, enterprise dashboards, and advanced analytics that support both internal management reporting and external regulatory requirements.
Job Description:
We are seeking a Senior Business Intelligence Analyst to design, build, and deploy analytics solutions across modern, cloud-based platforms. This role will focus on translating complex and often ambiguous business problems into production-ready data assets, actionable insights, and automated analytics solutions.
The ideal candidate combines strong technical expertise, analytical thinking, and business partnership skills to deliver measurable outcomes across regulatory reporting and internal risk management functions.
KEY ACCOUNTABILITIES
Develop scalable analytics solutions using Python, SQL, PySpark and PowerBI within cloud environments (Azure Databricks and enterprise data platforms)
Build curated datasets, automated pipelines, and analytics layers that support operational monitoring, performance insights, and regulatory controls
Analyze large, complex datasets to identify trends, risks, gaps, and optimization opportunities
Translate ambiguous business questions into structured analytical frameworks and actionable deliverables
Embed data quality checks, validation, and automation into all analytics products
Partner cross-functionally with RESL 2A / Policy business stakeholders, data engineering teams, and enterprise analytics groups
Communicate insights through dashboards, presentations, and executive-ready storytelling
Continuously improve analytics processes, standards, and reusable data assets
Support a strong risk and control culture through robust analytical monitoring and governance
EDUCATION & EXPERIENCE
Undergraduate degree in quantitative or technical discipline such as Mathematics, Statistics, Computer Science, Engineering, or Finance, graduate degree will be considered an asset.
3+ years of hands-on experience in Data Science, Data Analytics or Data Engineering roles, delivering scalable analytics solutions in complex environments
Strong programming skills in Python and SQL, with proven experience working with large and complex datasets
Experience with enterprise-scale cloud data platforms and understanding of associated tools, data structures, controls, and constraints (Azure Databricks is preferred)
Proven ability to apply statistical methods, machine learning techniques, and data wrangling to solve business problems and generate actionable insights
Experience designing and delivering data visualizations and dashboards (e.g., Power BI, Tableau) to communicate insights to both technical and non-technical stakeholders
Strong business acumen with the ability to translate ambiguous requirements into structured analytical solutions
Demonstrated experience working in cross-functional teams, including collaboration with business stakeholders, data engineers, and technology partners
Excellent communication and storytelling skills, with the ability to influence decision-making through data
RESL Business Knowledge will be considered an asset
Existing experience with RESL data architecture will be considered an asset
Td Bank · Toronto, Canada