Quantitative Consulting Lead: Model Risk & AI

Forvis-Mazars; Dallas (TX); On-site; USD 95,000 - 140,000; Full time

Job summary

Forvis Mazars, LLP is seeking a dynamic Senior Consultant to lead end-to-end model validation and governance within our Quantitative & AI Solutions team in the United States. The role partners with risk, finance, and technology stakeholders to strengthen validation, governance, and model operations for large financial institutions.

You will work on CECL, ALM/IRR, and liquidity models, delivering rigorous analyses and practitioner-level insights.

Qualifications

• Bachelor’s degree in a quantitative discipline, such as finance, economics, statistics, mathematics, engineering, or computer science.
• Proficiency with Microsoft Office suite applications.
• Two or more years of relevant professional experience.

Responsibilities

• Model validation and effective challenge: assess the soundness and limitations of model methodologies.
• Data inputs and assumptions review to ensure completeness and support.
• Testing and performance analysis, including back-testing and benchmarking.
• Model coverage across CECL, ALM/IRR, capital and liquidity models.
• Document testing results and recommendations for owners and executives.
• Prioritize workstreams and manage deadlines across engagements.
• Apply analytical and problem-solving skills to model risk issues.
• Communicate findings clearly in written and verbal form.

Skills

R

Python

SQL

Data analysis

Data validation

CFA/FRM

Education

Bachelor's degree in a quantitative discipline

Tools

Microsoft Office

Job description

Forvis Mazars, LLP is seeking a dynamic Senior Consultant to lead end-to-end model validation and governance within our Quantitative & AI Solutions team in the United States. The role partners with risk, finance, and technology stakeholders to strengthen validation, governance, and model operations for large financial institutions.

You will work on CECL, ALM/IRR, and liquidity models, delivering rigorous analyses and practitioner-level insights.