Hybrid Quantitative Risk Modeling Analyst

The Huntington National Bank; United States; Hybrid; USD 90,000 - 140,000; Full time

Job summary

The Huntington National Bank is seeking a Quantitative Risk Modeling Analyst to develop and monitor credit risk models for consumer and commercial portfolios. You will work with data scientists and risk partners to ensure model governance and validation readiness.

The role requires hands-on experience with SQL, SAS, R and Python, and a solid background in ML and data mining. You’ll report findings, support ad-hoc analyses, and contribute to risk framework improvements.

Qualifications

• Master's degree in a quantitative field.
• 1+ year experience in statistical modeling using SQL, SAS, R and Python.
• 1+ year experience in machine learning and data mining.
• 1+ year experience with data visualization tools (Tableau is preferred) and MS Office components (Excel vlookup, pivot tables, macros).

Responsibilities

• Development of consumer and/or commercial credit, PPNR, loan origination and portfolio management models.
• Analysis of credit portfolio performance data.
• Conducting ongoing monitoring of existing models.
• Analysis and reporting of ongoing monitoring results.
• Ability to work independently on projects with strict deadlines.
• Researching new modeling methodologies and techniques.
• Working with various teams within the firm to support governance, audit/compliance and validation projects related to the developed models.
• Completes analysis of credit portfolio performance data.
• Completes ad-Hoc analytics.
• Performs other duties as assigned.

Skills

SQL

SAS

R

Python

Machine Learning

Data Visualization

Excel

Statistics

Education

Master's degree in quantitative field

PhD in quantitative field

Tools

Tableau

MS Excel

Job description

The Huntington National Bank is seeking a Quantitative Risk Modeling Analyst to develop and monitor credit risk models for consumer and commercial portfolios. You will work with data scientists and risk partners to ensure model governance and validation readiness.

The role requires hands-on experience with SQL, SAS, R and Python, and a solid background in ML and data mining. You’ll report findings, support ad-hoc analyses, and contribute to risk framework improvements.