Data Scientist, Credit Risk Strategy (RESL) (ATH 5274)

Work Location: Toronto, Ontario, Canada Hours: 37.5 Line of Business: Risk Management 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 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: Role Overview This role leads strategic credit risk initiatives within the RESL portfolio, leveraging data, analytics, and emerging technologies to strengthen credit risk management, decision-making, and oversight. The role is well suited for someone who is naturally curious, enjoys solving complex problems, and can work comfortably with complex data to uncover meaningful risk insights and translate them into practical actions. The role requires strong hands-on analytical capabilities to support a range of risk management activities, including deep-dive analysis, ongoing monitoring and reporting, and data-driven support for testing, audit, and other risk reviews. Beyond analytics, the individual will contribute to strategic and transformation initiatives that leverage new technologies to enhance credit risk processes, controls, and decision-making. This requires the ability to quickly understand existing business processes, decision frameworks, policies, data, and control requirements, identify opportunities for improvement, and help define practical future-state solutions. Success in this role requires a combination of strong analytical thinking, adaptability, and sound and prudent risk judgment. The individual should be a quick learner who is comfortable navigating ambiguity, learning and applying new technologies, and connecting perspectives across risk, business, data, and technology. They are expected to challenge assumptions and constructively question the status quo, while balancing innovation with appropriate risk discipline and translating complex ideas into clear, practical, and executable outcomes. Ideal Candidate Profile The ideal candidate is a hands-on, analytically strong data scientist who can independently work with complex data, solve ambiguous problems, and turn analysis into meaningful risk insights and practical actions. They combine strong SQL and Python capability with sound risk judgment, intellectual curiosity, adaptability, and clear communication. They can quickly understand unfamiliar processes, policies, decision frameworks, data, and controls; apply new technologies to real business problems; and independently lead cross-functional work from problem definition through implementation. Key Accountabilities: Data Analysis & Risk Insights · Independently source, prepare, validate, and analyze complex data using SQL and Python. · Investigate complex credit risk questions, test hypotheses, identify trends and emerging issues, and determine their risk implications. · Translate analysis into clear, evidence-based recommendations and actions. · Develop and maintain accurate, timely, and decision-useful monitoring, reports, dashboards, and visualizations. · Provide data and analytical support for testing, audit, and other risk reviews. Risk Strategy & Transformation · Assess current processes, decision frameworks, policies, data, and controls to identify specific gaps and improvement opportunities. · Translate business and risk needs into clear requirements and practical future-state solutions that leverage data, analytics, AI, and emerging technologies. · Evaluate proposed solutions from a credit risk perspective, including decision impacts, data requirements, control gaps, and governance considerations. · Define a practical path from current state to implementation and support delivery through testing and rollout. Project Leadership & Stakeholder Management · Independently lead complex work from problem definition through analysis, recommendation, and implementation, with accountability for quality, timelines, and outcomes. · Work effectively across risk, business, data, regulatory reporting, operations, and technology teams to deliver results. · Communicate findings, trade-offs, risks, and recommendations clearly to technical and non-technical stakeholders, including senior leadership. · Use evidence and sound judgment to influence decisions and constructively challenge existing approaches. Required Qualifications · Bachelor's degree from an accredited university in mathematics, statistics, engineering, computer science, data science, or another STEM discipline. · Minimum 4 years of relevant professional experience. · Strong hands-on proficiency in both SQL and Python. The successful candidate must be able to independently extract, prepare, validate, analyze, and interpret complex data. · Demonstrated ability to structure ambiguous problems, test hypotheses, identify meaningful patterns, and draw well-supported conclusions. · Demonstrated ability to turn complex analysis into clear risk insights, recommendations, and actions. · Hands-on experience developing reports, dashboards, and data visualizations using Tableau, Power BI, or a comparable tool. · Demonstrated experience independently leading complex, cross-functional projects or workstreams from problem definition through delivery. · Strong written and verbal communication skills, including the ability to explain complex analytical and technical concepts to senior leaders and non-technical stakeholders. · Ability to learn unfamiliar business processes, policies, decision frameworks, data, controls, and technologies quickly. · Sound and prudent judgment, with the confidence to challenge assumptions constructively and recommend practical improvements. Preferred Qualifications · Experience in credit risk strategy, portfolio risk management, or a related risk discipline. · Experience applying AI-enabled or other emerging technologies to business processes, decision-making, or risk management. · Experience using Visio, Figma, or a similar tool to document processes, decision flows, frameworks, or operating models. What Success Looks Like · Complex data is converted into timely, accurate, and meaningful risk insights and actions. · Risk processes, decisions, controls, and oversight are strengthened through sound analysis and practical solutions. · Ambiguous problems are moved forward with clear requirements, recommendations, and executable paths. · Senior leaders and stakeholders receive concise, well-supported advice that enables informed decisions. Who We Are: TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities. Our Total Rewards Package Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD include