Senior Consultant, Quantitative Consulting

Forvis Mazars•Charlotte, NC

3d•Hybrid

About The Position

We are seeking a dynamic, client facing Quantitative Senior Consultant to join our Quantitative & Artificial Intelligence (AI) Solutions team. This role is designed for a well-rounded quantitative manager who combines deep, hands-on modeling expertise with the leadership and delivery discipline required to build, validate, govern, and run models in complex, highly regulated environments. You will work with large, systemically important financial institutions and other complex banking organizations, partnering with senior stakeholders across Risk, Finance, Treasury, Compliance, and Technology to strengthen their model development, model validation, model risk management (MRM), and model operations capabilities in alignment with SR 11-7 expectations. Model portfolios span traditional statistical approaches and advanced machine learning, and include key banking risk domains such as credit risk, market risk, and liquidity/treasury models. SR 11-7 emphasizes robust model development, implementation and use, effective independent validation, and strong governance, policies, and controls, all of which are central to this role. As a Senior Consultant, you will bring proven experience leading end-to-end model lifecycles, including hands-on development and independent validation of individual models, plus the operating model, controls, and tooling required to run MRM at scale.

Requirements

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.

Nice To Haves

Experience with data analysis, quantitative analysis, and data validation
Competency in programming in languages such as R or Python and database management such as SQL
CFA, FRM, or similar risk management-related credentials.
Prior consulting or professional services experience leading client engagements in model risk, validation, or quantitative analytics.

Responsibilities

Model validation and effective challenge: Assess the conceptual soundness, applicability, and limitations of mathematical and statistical model methodologies.
Data and assumptions review: Evaluate data inputs, assumptions, and model design choices to confirm they are appropriate, complete, and well supported.
Testing and performance analysis: Test computational accuracy and perform outcomes analysis, including back-testing, benchmarking, and sensitivity review as appropriate.
Model coverage: Validate and challenge a range of analytical models, including CECL, ALM/IRR, capital and liquidity stress testing, scorecard, compliance/regulatory, regression, and economic capital models.
Reporting and stakeholder communication: Document testing results, conclusions, limitations, and recommendations in clear reports for model owners, executives, and other key stakeholders.
Project execution: Prioritize multiple workstreams, manage competing deadlines, and maintain strong attention to detail across engagements.
Analytical rigor: Apply strong analytical, organizational, and problem-solving skills to complex quantitative and model risk management issues.
Communication: Present technical concepts and findings clearly through effective written and verbal communication.
Collaboration: Work effectively both independently and as part of a team in client-facing delivery environments.