Hybrid/Remote Quantitative Risk Modeling Analyst

Huntington National Bank; Columbus (OH); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Huntington National Bank is seeking qualified candidates for the role of Quantitative Risk Modeling Analyst. The position focuses on building and validating credit, PPNR, origination, and portfolio models, with emphasis on data-driven decisions and risk governance.

The team analyzes portfolio performance, monitors models, and delivers ad-hoc analytics while collaborating across departments. Candidates should have a strong quantitative background and programming skills in SQL, SAS, R, and Python.

Qualifications

• Master’s degree in quantitative field required.
• 1+ years of experience in statistical modeling using SQL, SAS, R and Python.
• 1+ years of experience in machine learning and data mining.
• 1+ years of experience with data visualization tools (Tableau preferred) and MS Office (Excel, pivots, macros).

Responsibilities

• Develop consumer and/or commercial credit, PPNR, loan origination and portfolio management models.
• Analyze credit portfolio performance data.
• Monitor existing models and report monitoring results.
• Work independently on projects with strict deadlines.
• Research new modeling methodologies and techniques.
• Support governance, audit/compliance and validation projects related to models.
• Complete ad-hoc analytics as needed.
• Perform other duties as assigned.

Skills

Statistical modeling

Machine learning

Data visualization

Programming

Education

Master’s degree in quantitative field

PhD in quantitative field

Tools

SQL

SAS

R

Python

Tableau

Excel

Job description

Huntington National Bank is seeking qualified candidates for the role of Quantitative Risk Modeling Analyst. The position focuses on building and validating credit, PPNR, origination, and portfolio models, with emphasis on data-driven decisions and risk governance.

The team analyzes portfolio performance, monitors models, and delivers ad-hoc analytics while collaborating across departments. Candidates should have a strong quantitative background and programming skills in SQL, SAS, R, and Python.