Credit Risk Model Manager

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Position Summary
The Credit Risk Analytics Manager is responsible for developing, maintaining, and enhancing the Bank’s credit risk models. This role partners with Lending, Technology, and Finance teams to deliver custom-tailored credit risk and projection models. The position plays a key role in credit risk modeling and governance, risk analytics, and data management initiatives.
Essential Duties and Responsibilities
Develop, implement, and maintain credit risk models using tools such as Python, SQL, Excel, and Moody's Analytics solutions (including RiskCalc, CMM, PortfolioStudio and related Moody's platforms).
Maintain comprehensive model governance documentation in accordance with SR 26-02 model risk management guidance, including model development documentation, methodology papers, conceptual soundness assessments, implementation testing, performance monitoring reports, user procedures, and inventory documentation.
Prepare analytical support and documentation for independent model validation, internal audit reviews, regulatory examinations, and management oversight committees. Respond to validation findings, tracking issues to resolution and ensuring corrective actions are appropriately documented and implemented.
Ensure all model inputs, calculations, assumptions, and reporting outputs are supported by transparent, reproducible, and auditable processes. Promote strong model governance practices that facilitate effective challenge, independent review, and examiner readiness.
Prepares periodic reports and/or dashboards utilizing PowerBI to monitor model performance, anomalies, inconsistencies, or unexpected results.
Performs other duties and responsibilities as assigned.
Qualifications
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.
Skills
Proficient in reviewing and interpreting model documentation and research materials with a strong focus on quantitative and statistical analysis.
Ability to read and interpret regulatory guidance and internal procedure documentation.
Ability to write routine reports, procedures and business correspondence.
Ability to respond in writing to audit findings customer complaints, regulatory agencies or member of the business community.
Ability to translate complex quantitative concepts into actionable and meaningful business insights.
Ability to effectively present information in one-on-one and small group situations, to customers, top management, public groups and/or boards of directors
Education and/or Experience
MS/MA degree; post graduate education in econometrics, quantitative finance, applied mathematics, statistics, or related field is preferred.
8+ years’ experience in loan portfolio/credit risk modeling, preferably at a financial institution.
Experience using Moody’s suite of credit risk models.
Technical Skills
Strong Excel and data analysis capabilities. MS Office programs.
Experience working with large datasets and relational databases utilizing SQL.
Knowledge of statistical and analytical techniques.
Competencies
Strong analytical and problem-solving skills.
Ability to communicate complex concepts to non-technical audiences.
Strong project management and organizational skills.
Detail-oriented with a focus on accuracy and governance.
Ability to work independently and manage multiple priorities.
Other
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Activities, duties and responsibilities may change at any time with or without notice.
Skills Training:
Communication, Critical Thinking, Judgment and Decision Making, Leadership, Management
Equal Employment Opportunity Information: Simmons First National Corporation and its subsidiaries are committed to a policy of equal employment with respect to a person's race, color, religion, sex, ancestry, sexual orientation, gender identity, national origin, covered veterans, military status, physical or mental disability or any other legally protected classifications.