Job Description

Closing Date (MM/DD/YYYY):


07/27/2025
Worker Type:


Permanent
Language(s) Required:


English
Term Duration (in months):


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