Data Scientist, ECL Modeling

Data Scientist, ECL Modeling page is loaded## Data Scientist, ECL Modeling locations:
500 Lake Shore Blvd W, Toronto, ONtime type:
Full time posted on:
Posted 11 Days Agotime left to apply:
End Date:
March 1, 2026 (15 days left to apply) job requisition :
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** Referred applicants should not apply directly to this role.
**** All referred applicants must first be submitted through Workday by a current Loblaw Colleague.
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* Location:

** 500 Lake Shore Boulevard West, Toronto, Ontario, M5V 2V9
** When you hire great people, great things can happen.
** PC Financial offers unprecedented value to Canadians through payment products. We're a different kind of bank with a different type of team—we’re collaborative and supportive and have the freedom and responsibility to thrive. Our purpose is to make the everyday simple and better for our customers, and we strive to make every dollar worth more.

Proudly serving over 3 million customers, PC Financial continues to grow by offering payment solutions and services that reward our customers every day. As a subsidiary of Loblaws Company Inc., we share the CORE values of Care, Ownership, Respect and Excellence. We are dedicated to helping Canadians Live Life Well. Join us on our journey.
** Why This Role is Important:
** Join our IFRS 9 team as Data Scientist, ECL Modeling, where you will play a pivotal role in shaping and executing on ECL (expected credit loss) modeling. You will oversee the development, enhancement, monitoring, and validation of ECL models, leveraging your skillset to provide data-driven insights for key provision decisions and effective credit risk management.

This role offers a challenging and rewarding experience, providing the opportunity to lead a team and make a significant impact on the bank's risk management framework.

** What You'll Do:
*** Lead the ECL enhancement roadmap for the team, in alignment with the overall business strategy by identifying and prioritizing key areas of focus.
* Lead, mentor, and manage a high performing team, fostering a culture of continuous learning and development.
* Apply statistical techniques and quantitative methods to validate, calibrate, and back test credit risk models.
* Oversee and conduct in-depth data analysis and interpret complex financial data to identify patterns, trends, and potential risks.
* Engage with senior executives, and business teams to present ECL results, model performance, and key risk insights to enable decision-making.
* Create insightful reports, presentations, and dashboards to communicate model outputs, findings, and recommendations effectively.
* Stay updated on emerging industry trends, regulatory changes, and advancements in credit risk modeling methodologies to continuously improve existing models.
* Collaborate with cross-functional teams to implement model enhancements and provide ongoing support for model performance monitoring and validation.

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* What You Bring:

*** Post-Secondary education in Statistics, Mathematics, or related quantitative field with 3+ years of experience in credit risk management or credit risk modeling
* Proven experience in applying credit risk modeling principles and techniques in accordance with accounting standards (IFRS 9 , CECL, etc.)
* Strong proficiency in statistical modeling techniques, data analysis, and quantitative methodologies.
* Proficient in programming languages which may include:
Python, R, SQL, SAS.

Experience with GCP (or other cloud) data services (Airflow, Big Query) is an asset.
* Excellent communication skills, with the ability to effectively convey complex concepts and findings to both technical and non-technical partners.
* Ability to distill and communicate complex analytic recommendations to both technical and non-technical stakeholders, both orally and in written presentations to influence decision-making

Come and join a winning team who demonstrates innovation, energy, creativity and vision.  We recognize the importance of a diverse workforce and we therefor encourage applications from Aboriginal Peoples, women, members of a visible minority and persons with a disability.  We thank all applicants for their interest, however, only those…