Michel W.

- Optimize and calibrate large-scale financial crime analytics models within the Agile ART framework to detect sophisticated transaction anomalies. - Engineer big data pipelines using Spark and Scala to scale real-time anti-fraud systems across massive enterprise infrastructure. - Leverage graph concepts and entity resolution patterns to map behavioral data across complex global transactions. - Technologies: Scala, Spark, Hadoop, Hive, Apache Oozie/Airflow, Elasticsearch, Bamboo CICD, Bitbucket, Bash, Oracle, SQL.

- Performed feature engineering on massive government and banking datasets to uncover hidden structural anomalies and fraud networks. - Optimized false-positive rates by tuning network-analytics models and entity resolution pipelines. - Managed cloud-native artifact distribution by leveraging MinIO (S3-compatible object storage) - Utilized AWS EC2 virtual servers and containerized cloud environments (Docker/Kubernetes) to build, test, and deploy scalable data pipelines. - Deployed a Quantexa solution at the Belgian Ministry of Finance (FOD Finance) to enable predictive risk-scoring for corporate and individual tax compliance. - Executed a Proof of Concept (PoC) at KBC Bank, implementing network analysis to flag fraudulent insurance and credit patterns. - Technologies: Quantexa, Scala, Spark, Hadoop, AWS EC2, MinIO (S3 Storage), Elasticsearch, SQL, TypeScript/Angular, Python, GitLab CICD, Docker/Kubernetes, Gradle.

- Conducted exploratory data analysis and data mining on raw banking logs to proactively identify emerging AML/KYC risk patterns. - Developed statistical fraud detection and transaction payment scoring algorithms to mitigate real-time card and payment fraud. - Engineered critical risk metrics and built complex relational Data Models using advanced DAX calculations. - Designed predictive compliance dashboards via SAP BusinessObjects and Excel Power Pivot to provide executive management with actionable insights. - Technologies: IBM Safer Payments, SAP BusinessObjects, Excel Power Pivot, DAX (Data Analysis Expressions), Data Modeling, Financial Analytics.

- Applied data mining methodologies to small and medium-sized enterprise (SME) datasets within the Belgian ICT sector. - Executed end-to-end data extraction and analytics to complete a Bachelor’s degree in Data Analysis at Haute École EPHEC. - Technologies: R, RStudio, Python, PowerBI, QlikSense, MS SQL, Excel/VBA.