Data Scientist, Credit Risk Strategy (RESL) (ATH 5274)
TD Bank is hiring a Data Scientist, Credit Risk Strategy (RESL) (ATH 5274) in Toronto, Canada. It pays CAD 97k-CAD 137k a year and Level rates it ; you can apply on TD Bank.
Level's read on this job
- Level rates this data scientist role Little AI ●○○○: aI is not part of the work.
- Tools and skills the posting cites include data science, credit risk and analytics.
- Level classifies it as a mid-level role.
- Level lists 1,700+ other open roles at TD Bank.
- The role was posted in the last few days.
AI in this role
Data Scientist leading credit risk strategy and analytics initiatives within the RESL portfolio.
Work Location:
Toronto, Ontario, CanadaHours:
37.5Line of Business:
Risk ManagementPay Details:
$96,900 - $136,800 CADTD 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 includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more
Additional Information:
We’re delighted that you’re considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.
Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.
Colleague Development
If you’re interested in a specific career path or are looking to build certain skills, we want to help you succeed. You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.
If you’re passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.
We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.
Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.
Interview Process
We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.
Accommodation
Your accessibility is important to us. Please let us know if you’d like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.
We look forward to hearing from you!
Language Requirement (Quebec only):
Sans ObjetHow we rate this
Data Scientist, Credit Risk Strategy (RESL) (ATH 5274) at TD Bank rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $167k
Use the typical data scientist figure as a reference when pay comes up. See data scientist jobs
Questions you could be asked
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where credit risk was part of your work. What did you do?
- Tell me about a project where analytics was part of your work. What did you do?
- Tell me about a project where risk management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Science, Credit Risk, Analytics, and Risk Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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