CRAFT / PROFESSION
AI & Data Engineer
Post-trade finance by profession — pipelines and data systems where accuracy is the entire job.
THE PRACTICE
How this craft shows up
By day I build the data plumbing behind post-trade finance: ingestion, validation, reconciliation — systems where a wrong number is not a bug report but a settlement failure.
Machine learning enters where rules run out: anomaly detection on breaks, classification on messy reference data, forecasting on volumes. Models serve the pipeline, never the other way round.
- Settlement-critical pipelines with validation gates
- ML for data quality: anomalies, breaks, forecasts
- Every run observable, every number explainable