Quantitative Model Risk Analyst

Rekruitd; Illinois; On-site; USD 95,000 - 160,000; Full time

Job summary

REKRUITD is seeking a Quantitative Model Risk Analyst to provide independent oversight of models used in banking and risk functions. You will review design, data, and performance, challenge results, and communicate findings to stakeholders. Strong Python skills and a quantitative advanced degree are required.

This full-time role in Illinois offers exposure to lending, credit risk, regulatory compliance, and other financial models, with opportunities to advance in model governance and automation.

Qualifications

• 1–3 years of experience in quantitative analysis, model validation or related fields.
• Hands-on experience with financial services models and data analysis.
• Advanced degree in a highly quantitative discipline required.

Responsibilities

• Review and validate quantitative models and methodologies across banking and risk functions.
• Assess design, data, calculations, controls and ongoing performance of models.
• Ch allenge model results with independent analysis and document conclusions.
• Perform quantitative testing and develop approaches to evaluate accuracy and stability.
• Collaborate with model developers, risk stakeholders, and business teams.
• Contribute to model governance, reporting, and regulatory support.
• Identify opportunities to improve validation processes and tooling.

Skills

Quantitative analysis

Model validation

Data science

Python

Strong communication

Education

Master's degree or PhD in Mathematics/Statistics/Economics or similar

Tools

Python

Job description

REKRUITD is partnering with one of our financial services clients to hire a Quantitative Model Risk Analyst for a full-time, permanent opportunity.

This role is part of an enterprise risk function responsible for providing independent oversight of models used to support business, risk, compliance, and financial decisions. We are looking for someone with a strong quantitative foundation who can analyze how models are designed, evaluate whether they are performing as intended, and clearly communicate potential risks or areas for improvement.

• Review quantitative models and analytical methodologies used across a variety of banking and risk functions.
• Assess model design, assumptions, underlying data, calculations, implementation, controls, and ongoing performance.
• Use independent analysis to challenge model results and determine whether methodologies are appropriate for their intended use.
• Perform quantitative testing and develop comparison approaches to evaluate model accuracy and stability.
• Review models supporting areas such as lending and credit risk, financial forecasting, regulatory compliance, financial crime, and valuation.
• Evaluate traditional statistical models as well as newer machine learning and AI-based approaches.
• Document your analysis and clearly communicate conclusions, identified risks, and recommended improvements.
• Partner with model developers, business teams, and risk stakeholders to understand methodologies and resolve findings.
• Contribute to the broader model governance program, including reporting and regulatory support.
• Look for ways to make validation and review processes more efficient through improved tools and automation.

Experience:

• 1–3 years of experience in quantitative analysis, model validation, model development, data science, or a similar area.
• Exposure to financial services models, particularly within areas such as credit risk, CECL, liquidity, compliance, BSA/AML, or fair lending.
• A Master's degree or PhD in Mathematics, Statistics, Economics, or another highly quantitative discipline.
• Hands‑on experience using Python for data analysis, modeling, or quantitative testing.
• Strong analytical skills and the ability to independently evaluate complex methodologies.
• Strong written communication skills with the ability to turn technical analysis into clear conclusions.
• Exposure to machine learning or AI modeling is a plus.

About the Opportunity:

This position offers the opportunity to work across a broad range of models and business areas while continuing to develop expertise in model risk and quantitative validation within the financial services industry.