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Open nowPosted 37 hours ago

Cross Model Analytics Model Developer

EURES job mobility portal554,643 open roles

Where
Groot-Rijnmond, Netherlands
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Your applicationOpen nowCross Model Analytics Model DeveloperEURES job mobility portal · Groot-Rijnmond, Netherlands
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Early applications get read.

10.1% of postings close within 7 days. Measured by our own scanner across the market. EURES job mobility portal postings stay open a median of 6 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.0%3 days
  3. 10.1%7 days
  4. 15.8%14 days
  5. 34.0%30 days
This job: posted 37 hours ago

EURES job mobility portal median: 6 days open

The posting

Finance Business Support Cross Model Analytics Model Developer 13-10-2026 5.677 - 9.137 Medior, Senior Amsterdam As a Model Developer Cross Model Analytics at ING, you coordinate development and maintenance for WB non-IRB credit risk models (IFRS9/Economic Capital), translate business and regulatory needs into model lifecycle design, and steer stakeholders on model choices and improvements. Direct solliciteren Neem contact op Automatisch verbeterd voor betere leesbaarheid Model Developer Cross Model Analytics Role purpose: Develop, validate, and maintain analytical models across multiple model types to support cross-model insights, performance monitoring, and decision-making. Key Responsibilities - Design, build, and deploy statistical and machine learning models for cross-model analytics and comparative evaluation. - Develop standardized frameworks for model performance measurement, benchmarking, and drift detection across portfolios. - Implement data pipelines and feature engineering processes to enable consistent model inputs and outputs. - Conduct model validation, back-testing, sensitivity analysis, and documentation to meet governance and audit requirements. - Collaborate with stakeholders to translate business needs into measurable modeling objectives and KPIs. - Automate reporting and monitoring dashboards to track model health, stability, and impact over time. - Ensure reproducibility through version control, testing, and robust deployment practices. Required Skills - Modeling: statistical modeling, machine learning, time series, and performance evaluation metrics. - Programming: Python and/or R; SQL for data extraction and transformation. - Data: feature engineering, data quality assessment, and scalable data processing. - Engineering: model lifecycle management, CI/CD concepts, and monitoring/alerting. - Communication: clear documentation and ability to explain model results to technical and non-technic...

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