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Open nowPosted 4 days ago

Data Scientist Compliance

EURES job mobility portal101,182 open roles

Where
Agglomeratie ’s-Gravenhage, Netherlands
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Your applicationOpen nowData Scientist ComplianceEURES job mobility portal · Agglomeratie ’s-Gravenhage, Netherlands

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on EURES job mobility portal's own form.

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 4 days ago

The posting

Finance Business Support Data Scientist Compliance 16-09-2026 6.378 - 8.504 Senior Den Haag As a Data Scientist Compliance at NN, you design, build and improve data analyses, dashboards and AI solutions for Compliance; translate risks into explainable models, ensure responsible AI (AI Act, risk assessments, controls), and own solutions end-to-end in production. Apply directly Contact us Data Scientist Compliance Role purpose Apply data science to strengthen compliance monitoring, risk detection, and regulatory reporting by developing transparent, auditable analytics and models that support governance and decision-making. Core responsibilities - Design, build, and maintain compliance analytics, risk scoring, and anomaly detection solutions. - Develop and validate statistical and machine learning models with clear documentation, explainability, and audit trails. - Partner with Compliance, Legal, Risk, and Engineering to translate regulatory requirements into measurable controls and data products. - Define data quality checks, monitoring metrics, and ongoing model performance reviews; manage drift and recalibration. - Create dashboards and reports for regulatory, internal audit, and leadership stakeholders. - Ensure responsible data use, privacy, and security practices across the analytics lifecycle. Required skills and qualifications - Strong proficiency in Python and SQL; experience with data pipelines and reproducible analysis. - Applied experience with machine learning, statistics, and model evaluation in regulated or risk-sensitive contexts. - Knowledge of compliance, governance, and risk concepts (e.g., AML, KYC, fraud, privacy, or regulatory reporting). - Experience with model explainability and documentation standards (e.g., feature importance, SHAP, model cards). - Ability to communicate complex findings to non-technical stakeholders and support audits. - Familiarity with data warehousing, BI tools, and versi...

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