Closing Date (MM/DD/YYYY):

07/27/2025

Worker Type:

Permanent

Language(s) Required:

English

Salary Range (plus eligible to receive a performance based incentive, applicable to position) :

Strong leader with a passion for mathematics and statistics needed
 

Mentor and lead team members and third-party consultants in a fast-paced, deadline-driven environment.
 

As an effective communicator and relationship-builder, you’ll strengthen model risk management practices across the organization in line with industry standards and approaches, providing confidence in FCC’s model suite and further enabling the business.

What you’ll do:

• Lead and oversee the Model Risk Management team, processes and lifecycle
• Oversee third-party engagements that support outsourced model validation work
• Maintain the standard for model risk management as a subject matter expert in the development and maintenance of the model risk policy and framework
• Ensure the model inventory is risk rated, assessed and validated to provide assurance to the business that models are fit for use
• Help leaders understand and leverage insights by clarifying complex data relationships that impact FCC and the industry through model management
• Collaborate in research and data sharing with internal and external stakeholders to keep pace with business and industry needs

What we’re looking for:

• Experienced leader committed to the success of others
• Confident communicator able to make complex information easy to understand
• Skilled collaborator able to build relationships across the organization and externally
• Deadline-driven multi-tasker who can ensure projects move forward under predetermined timelines in a fast-paced environment

What you’ll need:

• A professional designation (CFA, ASA, FSA) and/or graduate degree in business administration, mathematics, statistics or economics and at least seven years of related experience (or an equivalent combination of education and experience)
• Experience with model development and validation concepts and techniques, including a solid understanding of models used across economics, finance, marketing, risk management, credit risk modelling, credit portfolio management and IT
• Mastery of one or more predictive and descriptive analytics tools used to analyze large datasets
• Strong mathematical or statistical background