Credit Model Developer

First Horizon•Charlotte, NC

2d•Onsite

About The Position

Support the Credit Risk Models Team with the development, testing, implementation, monitoring, documentation, and maintenance of all credit risk models. These models are used for a variety of activities, including: CECL, stress testing, loss forecasting, origination, portfolio management, and economic capital. Responsibilities include sourcing, cleaning, and transforming data; researching applicable methods; training and testing a variety of specifications; documenting all facets of the development process; implementation of models and related logic in production systems; assessing outputs across different levels of inputs (sensitivity analysis and scenario analysis); back-testing and ongoing performance monitoring; and, communicating aspects of the model and its application to non-technical stakeholders.

Requirements

PhD or Master’s degree in Statistics, Econometrics, Mathematics or related quantitative field. A Bachelor’s degree in a quantitative field with additional certifications or experience may be considered.
Must have advanced quantitative statistical modeling skills (Regression, Time Series, Survival Analysis, Markov Chain, etc.)
PhD or master’s degree in Statistics, Econometrics, Mathematics or related quantitative field. A bachelor’s degree in a quantitative field with additional certifications or experience may be considered.
Experience with at least one of the following software packages: R, SAS, SQL, Python
Strong analytical and critical thinking skills with high attention to detail and accuracy
Excellent verbal, written, and interpersonal communication skills

Nice To Haves

2 or more years of model development or validation experience, particularly in credit risk or stress testing.
Working knowledge of Python, R, SAS, and SQL.
Working knowledge of Generally Accepted Accounting Principles (GAAP), Basel III, Dodd-Frank Act Stress Testing, CCAR, and bank accounting/regulatory reporting requirements.
Ability to clearly articulate, in writing or orally, ideas, analytic insights, and recommendations to both technical and non-technical audiences, including an executive audience.
Ability to use advanced statistical and mathematical software to perform descriptive, predictive, and prescriptive analysis leveraging a variety of statistical techniques (such as segmentation, logistic regression, sensitivity analysis, and machine learning).
An ability to identify key problems, conduct in-depth research, and articulate well-reasoned solutions.
Knowledge of Python, R, SAS, or SQL
Proficiency in the use of Microsoft Office with advanced experience in Excel
Familiarity with software version control systems, such as Git

Responsibilities

Develop and apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data sets from multiple sources (including internal consumer, mortgage, and commercial loan systems, external bank data (e.g., Call Reports), and economic forecasts) to develop credit risk models for CECL, stress testing, scorecards, economic capital, or other credit risk-related initiatives.
Derive model assumptions that are well reasoned and supportable.
Implement models in code in a transparent and easily maintainable way.
Comprehensively and clearly document all modeling or analysis work that meets internal, GAAP, and regulatory requirements; translate model theory and related results for non-quantitative audiences.
Develop and support strong controls for the model implementation framework and maintain related documentation.
Support independent model validation process, internal and external audits, and regulatory reviews.
Interact with model owner/users, validators, and regulators to address model issues and remediation actions.
Interact with key stakeholder groups such as Accounting, Treasury, Credit, Lines of Business, Model Risk Management, and Enterprise Technology in the design, development, and ongoing usage of models.
Monitor the performance and calibration of existing models.
Work on various ad hoc quantitative, modeling, and programming assignments.