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Open nowPosted 39 hours ago

Risk Model Expert

EURES job mobility portal376,369 open roles

Where
Groot-Amsterdam, Netherlands
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Your applicationOpen nowRisk Model ExpertEURES job mobility portal · Groot-Amsterdam, Netherlands

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The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. EURES job mobility portal postings stay open a median of 3 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.6%3 days
  3. 8.1%7 days
  4. 15.1%14 days
  5. 34.0%30 days
This job: posted 39 hours ago

EURES job mobility portal median: 3 days open

The posting

Risk Model Expert As a Risk Model Expert at NN Group you develop and enhance the internal risk model, covering credit, equity, longevity and persistency risks, and act as an internal risk consultant to align models with the risk profile and support implementation and use. Apply directly Contact us Automatisch verbeterd voor betere leesbaarheid Risk Model Expert Role purpose: Design, validate, and maintain risk models that support sound decision-making, regulatory compliance, and effective risk management across the organization. Key responsibilities - Develop, enhance, and document quantitative risk models (e.g., credit, market, liquidity, operational) across the model lifecycle. - Perform model validation, back-testing, benchmarking, and sensitivity analysis; identify limitations and propose remediation. - Monitor model performance and stability; define thresholds, alerts, and ongoing monitoring frameworks. - Translate business and regulatory requirements into model specifications, assumptions, and data needs. - Partner with stakeholders (risk, finance, analytics, IT) to ensure model governance, approvals, and audit readiness. - Ensure data quality and lineage; support model implementation and production controls. - Prepare clear reporting for model risk committees and senior leadership. Required skills and qualifications - Risk modeling expertise: statistical modeling, risk quantification, and model risk management. - Methods: regression, time series, scorecards, machine learning fundamentals, stress testing, scenario analysis. - Tools: Python and/or R, SQL; familiarity with model deployment and version control is preferred. - Data: feature engineering, data validation, and reproducible analysis. - Governance: model documentation, validation standards, and regulatory expectations. - Communication: ability to explain complex models to non-technical audiences. Note: Please provide the full job description text to tailor resp...

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