Quantitative Analyst – Model Risk
$90,000–$110,000 annually
ApplyQuantitative Analyst – Model Risk
Posted 3 days ago
SENIORITY
Senior
SALARY
$90,000–$110,000 annually
About the role
- Independently validate statistical, econometric, mathematical, machine learning, and qualitative models
- Evaluate models for conceptual soundness, implementation accuracy, data integrity, governance, and performance
- Develop and execute model validation approaches and benchmark models based on model complexity and risk
- Perform quantitative testing including back-testing, sensitivity analysis, scenario analysis, and benchmarking
- Review models supporting areas such as credit risk, CECL, stress testing, AML/BSA, fair lending, customer risk, liquidity, and valuation
- Prepare detailed model validation documentation outlining methodology, testing, findings, conclusions, and recommendations
- Partner with model developers, business stakeholders, and risk teams to investigate findings and drive issues toward resolution
- Support model governance activities and reporting for senior leadership, risk committees, and regulatory examinations
- Identify opportunities to automate and improve model validation processes
- Assist with the evaluation and validation of emerging AI and machine learning models
- Master’s degree or PhD in Mathematics, Statistics, Economics, Data Science, or another quantitative discipline
- Approximately 1–3 years of relevant experience in quantitative analysis, data science, model development, or model validation1–2+ years of hands-on Python experience
- Understanding of statistical modeling, econometrics, machine learning, and quantitative testing methodologies
- Experience or exposure to financial risk models such as:
- Consumer or commercial credit riskCECLStress testing
- LiquidityBSA/AMLFair lending
- Ability to evaluate model assumptions, methodology, data, implementation, and performance
- Strong analytical, problem-solving, and technical documentation skills
- Ability to clearly communicate quantitative findings to both technical and nontechnical stakeholders
- Previous experience within banking, financial services, risk management, or another regulated industry
- Direct experience with model development or independent model validation
- Exposure to AI or machine learning model validation
- Familiarity with financial-services model risk management and regulatory expectations
- Experience automating quantitative analysis or validation processes using Python
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
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A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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