Credit Risk Specialist (Credit Automation) (ATH 5028)

TD•Toronto, ON

11d•CA$96,900 - CA$136,800•Onsite

About The Position

The TDAF Credit Risk Automation team is helping shape the future of automotive lending at TD. We design, implement and oversee automated risk decisioning strategies that enable faster, more consistent credit decisions while supporting responsible growth, dealer and customer experience, operational efficiency and strong portfolio performance. Working across Risk, Product, Technology, Data, Model Development and Operations, the team turns advanced analytics, machine-learning models and emerging data capabilities into well-governed credit solutions across Prime, Non-Prime, Lease and Recreational lending. The opportunity Reporting to the Senior Manager, TDAF Credit Risk Strategy, you will play a hands-on leadership role in advancing TDAF's credit automation agenda. You will translate portfolio insights, advanced scoring models and business priorities into automated risk decisions that improve speed, consistency and scalability while protecting the Bank's risk appetite. This is an opportunity to work at the intersection of credit risk, data science and digital transformation. You will influence how credit decisions are made, partner with senior stakeholders and see your work move from analysis and design through testing, implementation and ongoing optimization.

Requirements

Four or more years of relevant experience in retail credit risk, lending strategy, decision science, analytics, product management or a related financial-services discipline.
Understanding of credit risk fundamentals and the ability to connect policy, strategy, portfolio performance and customer outcomes.
Demonstrated experience using data to solve ambiguous business problems and convert analysis into practical recommendations.
Good SQL and Python skills.
Strong project leadership and stakeholder-management skills, with the ability to coordinate across Risk, Business, Technology, Data and Operations.
Clear, persuasive written and verbal communication, including the ability to explain complex analysis to non-technical and senior audiences.
Intellectual curiosity, sound judgment, attention to detail and a strong ownership mindset.
Comfort working in an agile environment, managing changing priorities and escalating risks or issues early.
Post-secondary degree in a quantitative, business or technology-related field, such as Mathematics, Statistics, Economics, Finance, Engineering or Computer Science.

Nice To Haves

Experience with SAS, Power BI, Tableau or similar tools is an asset.
Familiarity with machine-learning techniques such as decision trees or XGBoost, model implementation, cloud analytics or big-data environments is a strong asset.
Experience with Azure platforms is an asset.
Experience designing, monitoring, validating or governing automated adjudication strategies is an asset; automotive finance experience is welcome but not required.
A master's degree or relevant professional designation is an asset, not a requirement.

Responsibilities

Lead the design, development, testing, implementation and enhancement of acquisition and account-management automated risk decision strategies across TDAF portfolios.
Use portfolio, application, bureau, internal TD and performance data to identify opportunities to increase automation, strengthen risk segmentation and improve dealer and customer outcomes.
Evaluate and enable advanced scoring solutions, including Hubble, Webb and other machine-learning or alternative-data capabilities, within scalable decisioning frameworks.
Monitor auto-adjudication, approval, decline, manual-review, delinquency and loss outcomes; investigate emerging trends and recommend timely, evidence-based action.
Balance growth, profitability, operational efficiency and client experience with prudent credit risk management and effective challenge.
Lead strategy simulations, impact assessments, testing, first-occurrence verification and post-implementation reviews to confirm solutions perform as intended.
Maintain clear strategy documentation, controls, audit trails and monitoring that support ARD, model, policy and regulatory governance.
Represent Retail Risk Management as a trusted subject-matter expert for new products, platform modernization and strategic initiatives.
Collaborate across TDAF Product, Decision Optimization, Technology, Data, Model Development, Operations, Policy, Governance and external partners to move complex initiatives from concept to implementation.
Communicate concise insights and recommendations to senior leadership, translating technical analysis into clear business and risk decisions.
Contribute to an inclusive, curious and high-performing team culture where colleagues own risk, raise issues early and continuously improve how work gets done.