Quantitative Risk Modeling Analyst

Huntington National Bank

. Develop consumer and/or commercial credit, PPNR, loan origination and portfolio management models .

Posted 9/21/2026full-timeUnited StatesJuniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in statistical modeling and machine learning, with proficiency in SQL, SAS, R, and Python. Strong analytical skills and experience in credit portfolio management, data visualization, and compliance frameworks.

Highest-signal resume keywords

Statistical ModelingMachine LearningData VisualizationSQL ProgrammingCredit Portfolio Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningData AnalysisSQLSASRPythonData VisualizationExcelPortfolio Management

Soft Skills

Analytical SkillsCommunication SkillsMultitasking

Tools & Technologies

TableauMS Office

Industry Keywords

CCARDFASTCECLLoss ForecastingLoan Origination

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Develop consumer and/or commercial credit, PPNR, loan origination and portfolio management models
Analyze credit portfolio performance data
Conduct ongoing monitoring of existing models
Analyze and report ongoing monitoring results
Work independently on projects with strict deadlines
Research new modeling methodologies and techniques
Work with various teams within the firm to support governance, audit/compliance and validation projects related to developed models
Complete ad hoc analytics
Perform other duties as assigned

Requirements

What you’ll need

Master’s degree in quantitative field (mathematics, statistics, economics, engineering, finance, physics)
1+ years of experience in statistical modeling using SQL, SAS, R and Python that may be a combination of work experience and/or study project
1+ years of experience in machine learning and data mining
1+ years of experience with data visualization tools (Tableau is preferred) and MS Office components (Excel vlookup, pivot tables, macros)
Applicants must be currently authorized to work in the United States on a full-time basis
PhD in quantitative field (preferred)
Knowledge of CCAR/DFAST and CECL concepts and frameworks (preferred)
Knowledge of loss forecasting, loan origination and portfolio management modeling concepts and methodologies (PD, LGD, EAD) (preferred)
Demonstrated strong analytical skills
Demonstrated experience and competence in programming using SQL, SAS, R, and Python
Strong communication skills
Proficiency in MS Office products
Fundamental understanding of economic concepts
Fundamental understanding of risk concept and framework
Ability to multitask and work efficiently