Senior Quantitative Model Analyst - Treasury Forecasting

US Bank; Charlotte (NC); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Healthcare

Retirement plan

Paid vacation

Sick leave

Holiday allowance

Job summary

U.S. Bank in Charlotte, NC is seeking a seasoned quantitative analyst to build and maintain advanced statistical models for balance sheet forecasting and interest-rate risk analysis within Corporate Treasury.

You will present modeling approaches to stakeholders, document methodologies, and collaborate across teams to support strategic financial decisions in a fast-paced banking environment. Applicants should have a quantitative degree and extensive experience in regression, times series methods,

Qualifications

• Bachelor's degree in a quantitative field and five or more years of relevant experience.
• MA/MS in a quantitative field and three or more years of related experience.
• PhD in a quantitative field and less than two years of related experience.

Responsibilities

• developing and maintaining advanced statistical models used for balance sheet forecasting and interest rate risk analysis.
• communicating modeling approaches and results to stakeholders across the bank; deliverables include documentation, reports, and code.

Skills

Regression techniques

Time series

Model validation

Python

Data compilation

Programming skills

Risk factors knowledge

Regulatory knowledge

Task management

Analytical skills

Communication

Team leadership

Education

Bachelor's degree in a quantitative field

MA/MS in a quantitative field

PhD in a quantitative field

Tools

Python

Job description

U.S. Bank in Charlotte, NC is seeking a seasoned quantitative analyst to build and maintain advanced statistical models for balance sheet forecasting and interest-rate risk analysis within Corporate Treasury.

You will present modeling approaches to stakeholders, document methodologies, and collaborate across teams to support strategic financial decisions in a fast-paced banking environment. Applicants should have a quantitative degree and extensive experience in regression, times series methods,