Quantitative Risk Director — Financial Services

Scovai; Chicago (IL); Hybrid; USD 180,000 - 280,000; Full time

Job summary

Scovai in Chicago is seeking a Quantitative Risk Director to lead model risk and quantitative risk management in a hybrid work environment. The role focuses on model validation, VaR/ES, CCAR/DFAST, and Basel SR 11-7 governance, directing regulators and internal audit where needed.

You will build and lead a team of quantitative analysts and partner with risk technology and front-office quants, presenting methodology and results to senior management and risk committees.

Qualifications

• Lead model risk governance and validation across risk classes.
• Own VaR and expected shortfall methodology and regulatory stress testing.
• Build and lead a team of quantitative analysts; interact with board committees.

Responsibilities

• Oversee CCAR/DFAST submissions and internal stress-testing cycles.
• Present risk methodology and results to senior management and boards.
• Roadmap risk analytics infrastructure and ML integration where applicable.

Skills

Model risk management

Quantitative analysis

Leadership

Regulatory reporting

Stakeholder communication

Education

Advanced degree in Financial Engineering/Statistics/Mathematics/Physics

Tools

CCAR/DFAST

SR 11-7/Basel

Job description

We are conducting a confidential search for a Quantitative Risk Director to lead model risk and quantitative risk management for a financial services organization based in Chicago, working hybrid. This is a director-level opportunity for a quant risk leader who can own model validation, capital adequacy analytics, and regulatory stress testing.

In this role, you will lead the model validation function across credit, market, and counterparty risk models, own the methodology for Value-at-Risk (VaR) and expected shortfall calculations, and direct the bank's participation in CCAR/DFAST and internal stress-testing cycles. You will oversee model risk governance under SR 11-7/Basel frameworks, manage relationships with regulators and internal audit on model risk matters, and ensure model inventories, documentation, and back-testing meet regulatory expectations.

You will build and lead a team of quantitative analysts and model validators, partner with front-office quants and risk technology teams on model implementation, and present risk methodology and results to senior management and board risk committees. You will also drive the roadmap for risk analytics infrastructure and machine-learning-based risk models where applicable.

Nice to Have:

• Experience with CCAR/DFAST submission cycles at a bank or systemically important institution
• Advanced degree in a quantitative field (Financial Engineering, Statistics, Mathematics, Physics)
• FRM or PRM certification
• Experience integrating machine learning into traditional risk models
• Direct experience presenting to board-level risk committees

Nice to have

• Experience with CCAR/DFAST submission cycles at a bank or systemically important institution
• Advanced degree in a quantitative field (Financial Engineering, Statistics, Mathematics, Physics)
• FRM or PRM certification
• Experience integrating machine learning into traditional risk models
• Direct experience presenting to board-level risk committees