Data Scientist - Data Science - F/H
Farm Credit Canada
About the role
Employment Type
Permanent
Language(s) Required
English
Salary Range
(plus eligible to receive a performance based incentive, applicable to position) :
About FCC
At FCC, we’re proud to be 100% invested in Canadian agriculture and food. As a federal Crown corporation, we provide financing, knowledge resources and business management software to over 103,000 customers nationwide.
Benefits
- Competitive total rewards packages: market-aligned and performance-based salary and incentive programs, flexible and comprehensive group benefit and savings plans, and well-being support through benefits and wellness programs
- Learning and development opportunities to help you thrive
Role Overview
As a Data Scientist, you’ll focus on building and improving tools to help FCC understand and manage credit risk. Working with complex data, you’ll design and validate analytical models that directly support risk management and data‑driven decision making. Your work will help assess, monitor, and mitigate credit risk throughout FCC, as models are implemented in real‑world operations through close collaboration with business and technology teams. You’ll deliver clear, actionable insights that inform strategic and operational decisions and drive measurable improvements in portfolio risk outcomes.
Responsibilities
- Design, develop, validate , and maintain credit risk models, including Internal Rating and Operational Credit Risk Models , Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), and analyze how these components interact.
- Unlock insights from complex internal and external data to support data‑driven decision‑making.
- Apply advanced analytics techniques (e.g., statistical modeling, machine learning, forecasting) to identify risks and opportunities.
- Translate complex analytical outputs into clear, practical insights for non‑technical stakeholders.
Qualifications
- Bachelor’s degree in finance, economics, mathematics, statistics, actuarial science, computer science, agriculture , or a related field.
- 4+ years of experience in data science, analytics, or risk modeling, including experience in developing credit risk models .
- Strong understanding of Internal Rating, PD, LGD, and EAD, and their role in credit risk measurement frameworks , including IFRS 9 and Economic Capital .
- Proven experience building, validating , and interpreting statistical or predictive models.
- Strong foundation in statistics, mathematics, and analytical problem‑solving.
- Proficiency with tools such as SQL, SAS, R, Python, Power BI, or similar technologies.
- Strong written communication skills, with experience producing clear, high-quality model development and validation documentation
Preferred Experience
- AWS).
- Experience supporting domains such as risk management, marketing and pricing, economics, finance, or strategy.
- Experience mentoring or providing technical leadership to other analytics professionals.
Equity Statement
At FCC, we’re committed to creating an inclusive, equitable and accessible workplace - one that reflects the communities where we live, work and play. Our team is made stronger through diversity, and we’re dedicated to building a workforce that brings together a range of backgrounds, abilities and perspectives.
We encourage qualified applicants to apply, including members of these four employment equity groups:
- Indigenous Peoples
- Persons with disabilities
- Women
Accommodation
To support an inclusive and accessible candidate experience, we encourage anyone needing an adjustment or accommodation during any stage of the recruitment process to email us at:
Requirements
- Strong understanding of Internal Rating, PD, LGD, and EAD, and their role in credit risk measurement frameworks, including IFRS 9 and Economic Capital.
- Proven experience building, validating, and interpreting statistical or predictive models.
- Strong foundation in statistics, mathematics, and analytical problem-solving.
- Proficiency with tools such as SQL, SAS, R, Python, Power BI, or similar technologies.
- Strong written communication skills, with experience producing clear, high-quality model development and validation documentation.
Responsibilities
- Design, develop, validate, and maintain credit risk models, including Internal Rating and Operational Credit Risk Models, Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), and analyze how these components interact.
- Unlock insights from complex internal and external data to support data-driven decision-making.
- Apply advanced analytics techniques (e.g., statistical modeling, machine learning, forecasting) to identify risks and opportunities.
- Translate complex analytical outputs into clear, practical insights for non-technical stakeholders.
Benefits
Skills
Don't send a generic resume
Paste this job description into Mimi and get a resume tailored to exactly what the hiring team is looking for.
Get started free