Remote Model Risk Analyst | Validate & Safeguard Models

UMB Financial Corporation; Kansas City (MO); Remote; USD 82,000 - 120,000; Full time

Benefits offered by this job

Paid Time Off

401(k) matching

Medical, dental, vision insurance

Job summary

UMB Financial Corporation in Kansas City, MO seeks a Model Risk Analyst to independently validate models across the organization. You will perform conceptual soundness assessments, methodology reviews, data quality checks, and ongoing performance monitoring to support informed decisions.

You will collaborate with line-of-business partners, model developers, and risk teams, applying statistical techniques and staying current with AI/ML developments to oversee risk across the model life cycle.

Qualifications

• Bachelor’s degree in Statistics/Applied Mathematics, Finance, Economics or equivalent.
• 2+ years of experience in risk management processes, model development/validation, consulting, banking, or financial services.

Responsibilities

• Model Validation: Perform independent model validations and monitoring.
• Quantitative Analysis: Apply statistical and analytical techniques to evaluate model performance.
• Model Risk Assessment: Identify, document, and evaluate model risks and control findings.
• Model Monitoring: Review ongoing model performance, back-testing, and sensitivity analyses.
• Business Partnership: Collaborate with model owners, developers, and risk teams to communicate findings.
• Emerging Technology: Contribute to oversight of AI/ML and advanced analytical models.

Skills

Python

R

SAS

SQL

AI tools

Statistical analysis

Education

Bachelor’s degree in Statistics/Applied Mathematics, Finance, Economics

Job description

UMB Financial Corporation in Kansas City, MO seeks a Model Risk Analyst to independently validate models across the organization. You will perform conceptual soundness assessments, methodology reviews, data quality checks, and ongoing performance monitoring to support informed decisions.

You will collaborate with line-of-business partners, model developers, and risk teams, applying statistical techniques and staying current with AI/ML developments to oversee risk across the model life cycle.