Quantitative Risk & Model Validation Consultant

Forvis Mazars US; Charlotte (NC); On-site; USD 120,000 - 180,000; Full time

Job summary

Forvis Mazars, LLP seeks a Quantitative Consultant to join the Quantitative & AI Solutions team. You will lead end-to-end model lifecycles, validate models, review data and assumptions, and communicate results to senior stakeholders in risk, finance, and technology.

The role spans traditional statistics and machine learning across credit, market, and liquidity models, with emphasis on governance, controls, and independent validation to support MRM at scale.

Qualifications

• Experience with data analysis, quantitative analysis, and data validation.
• Programming in R or Python and SQL database management.

Responsibilities

• Model validation and effective challenge: assess soundness, applicability, and limitations of models.
• Data and assumptions review: evaluate inputs and design choices for completeness and support.
• Testing and performance analysis: run back-testing and sensitivity analyses.
• Model coverage: validate CECL, ALM/IRR, capital and liquidity stress tests, scorecards and regulatory models.
• Reporting and stakeholder communication: document results for owners and executives.
• Project execution: prioritize workstreams and manage deadlines.
• Analytical rigor: apply rigorous analysis to model risk issues.
• Communication: present findings clearly in writing and verbally.
• Collaboration: work independently and in client-facing teams.

Skills

Data analysis

Quantitative analysis

Data validation

R

Python

SQL

Microsoft Office

Education

Bachelor's degree in quantitative field

CFA

FRM

Tools

Microsoft Office

Job description

Forvis Mazars, LLP seeks a Quantitative Consultant to join the Quantitative & AI Solutions team. You will lead end-to-end model lifecycles, validate models, review data and assumptions, and communicate results to senior stakeholders in risk, finance, and technology.

The role spans traditional statistics and machine learning across credit, market, and liquidity models, with emphasis on governance, controls, and independent validation to support MRM at scale.