Consultant, RESL Advanced Analytics (Toronto)

Consultant, RESL Advanced Analytics

Location: Toronto, ON

Job type: Full time

Posted on: Today

End Date: July 2, 2026 (8 days left to apply)

Job Requisition ID: 2612930

What you'll be doing

You’ll be part of the Real Estate Secured Lending Advanced Analytics team within Risk Analytics and Credit Decisioning (RACD). As a Consultant, you act as a subject matter expert and provide consultative and technical advice; assess the impact, effectiveness and feasibility of proposed changes. You’ll recommend decisions and provide support based on thorough analytics results. You use independent judgement to determine methods and approaches to work. You’ll participate in and/or facilitate internal/external meetings with key stakeholders at various levels, taking ownership of activities to ensure client needs are met or exceeded. You’ll work closely with various functional groups within RACD to fully understand business needs and advocate for solutions that align with the business objectives.

How you’ll succeed

• Quantitative Modeling and Analytics – Leverage advanced quantitative modeling and analytical techniques to monitor portfolio performance, interpret complex data, identify and forecast key portfolio risk trends.
• Strategy Development – Perform in-depth quantitative analysis to support the design and execution of both acquisition and account management strategies, optimizing risk‑reward tradeoffs for all retail lending products through robust champion/challenger methodologies.
• Project Management – Take full ownership of project portfolios by applying project management best practices, ensuring effective planning, execution, control, and closure of projects.
• Stakeholder Management – Collaborate effectively with peers, management, and cross‑functional partners to identify business needs, address issues, and ensure successful initiative implementation.

Who you are

• Experienced in Advanced Analytics – You have hands‑on experience in advanced data analytics, with a Bachelor’s degree or higher in Data Analytics, Data Science, Applied Mathematics, or a related field, and 3–5 years of experience working with large‑scale data. Experience in the banking industry, particularly in retail credit risk management, is considered an asset.
• Technically Proficient – Skilled in using analytics and business intelligence tools such as Data Bricks, Python, SQL, SAS, Power BI or Tableau to extract, manipulate, and visualize data.
• Insightful and Analytical – Passionate about uncovering insights from complex data, enjoy solving challenging problems, and excel at translating detailed information into clear, actionable recommendations.
• Ownership Mindset – Results‑driven, takes initiative, and demonstrates a strong sense of ownership in your work. Motivated to achieve goals and deliver impactful outcomes.
• Values matter – Brings your real self to work, living out the values of trust, teamwork, and accountability.

What CIBC Offers

• Competitive salary, incentive pay, banking benefits, a benefits program, defined benefit pension plan.
• Employee share purchase plan, vacation offering, wellbeing support, and MomentMakers social recognition program.
• Paid purpose day for personal growth and development.
• Technological toolkit and collaborative spaces designed for innovative solution development.

CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation, please contact View email address on ca.talent.com. CIBC is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise.

Job Location: Toronto – 81 Bay, 29th Floor. Employment Type: Regular Weekly Hours: 37.5. Skills: Analytical Thinking, Business Requirements, Communication, Data Quality, Delivery Management, Prioritization, Quality Improvement, Risk Analytics, Risk Reporting, Test Planning.