Credit Data & Risk Analyst II

First National Bank of Omaha; Omaha (NE); Hybrid; USD 63,000 - 104,000; Full time

Benefits offered by this job

Medical

Dental

Vision Insurance

401k, With Matching Contributions

Time Off Programs

Health Savings Account (HSA)/Dependent

Growth Opportunities

Tuition Assistance

Short-Term/Long-Term Disability

Job summary

First National Bank of Omaha is seeking an Analyst II to support credit analytics and reporting for the credit team. You will collect, process and analyze credit data to generate actionable insights and monthly reports, assisting senior staff with QA/QC and data quality assessments.

Based in Omaha with a hybrid schedule, this entry-level role focuses on analyzing credit card loan portfolios, identifying trends, and building a foundation for growth within credit risk through data-driven decision

Qualifications

• Bachelor's degree in Statistics, Data Science, Mathematics, Finance, Business or related field
• 1+ year of experience in credit analytics, risk management, or a related field
• 1+ year experience working with analytical tools (e.g., SQL, R, Python)

Responsibilities

• Conduct analysis and reporting work as assigned, including helping run regular monthly reporting
• Monitor ongoing delinquency and loss performance of credit card portfolios, identify and investigate trends and report on findings

Skills

Analytical thinking

Independent researcher

Education

Bachelor's degree in Statistics/Data Science/Mathematics/Finance/Business

Advanced degree preferred

Tools

SQL

Python

R

Job description

First National Bank of Omaha is seeking an Analyst II to support credit analytics and reporting for the credit team. You will collect, process and analyze credit data to generate actionable insights and monthly reports, assisting senior staff with QA/QC and data quality assessments.

Based in Omaha with a hybrid schedule, this entry-level role focuses on analyzing credit card loan portfolios, identifying trends, and building a foundation for growth within credit risk through data-driven decision