Base: approximately €100k–€150k py; bonus/equity: ...
Hybrid
Deep expertise in market risk models
Strong quantitative background in statistics
Experience in heavily regulated environments
ING is seeking a Senior Model Validator for its Model Validation Financial Risk department in Amsterdam, focusing on Market Risk and Trading Book financial risk models. The role requires strong quantitative expertise, stakeholder engagement, and experience in a regulated environment, with an emphasis on model validation and risk management
Job Summary
This role involves validating Trading Book financial risk models end-to-end, covering Market Risk, CCR, and Pricing & Valuation.
The successful candidate will act as a Lead Validator, owning validations from planning to closure while challenging model developers on risk perspectives.
The position offers a competitive total compensation package ranging from approximately €100k to €150k per year with hybrid working flexibility.
Matching Summary
Match Score: 85
ING is seeking a Senior Model Validator for its Model Validation Financial Risk department in Amsterdam, focusing on Market Risk and Trading Book financial risk models. The role requires strong quantitative expertise, stakeholder engagement, and experience in a regulated environment, with an emphasis on model validation and risk management.
Salary
Base: Approximately €100k–€150k per year; Bonus/Equity: Not specified; Benefits: 25-28 vacation days, Pension scheme, 13th month salary, 8% Holiday payment
Skills & Requirements
Must-have
Deep expertise in Market Risk models
Strong quantitative background in statistics
Experience in heavily regulated environments
Ability to translate complex analysis for committees
End-to-end validation of Trading Book models
Nice-to-have
Proactive and accountable mindset
Collaborative attitude with coaching interest
Innovation in automation or AI-enabled validation
Trusted sparring partner approach
Key Requirements
Deep expertise in Market Risk
Solid understanding of Trading Book financial risk models
Experience in heavily regulated environment
Strong quantitative background in financial mathematics or econometrics