Netherlands
I'm a Machine Learning and Quantitative Finance consultant, and I work with asset managers, trading firms, banks, pension funds, governments, and energy companies across Europe. I've held a range of roles over the years: I started out trading options on the exchange floor, later led the modelling and research department at a large European energy trading firm, and now spend most of my time building models, algorithms and platforms. I'm a Kaggle Master (top 0.1%), a contributor to the open-source Boost C++ libraries, and a two-time winner of the Dutch National Science Quiz.
Simu.ai builds fast, accurate pre-trained neural models for quantitative finance and other simulation-heavy domains. We help organisations convert slow or complex models, pricing engines, risk systems, optimisation models, simulation environments into compact neural approximations that run in real time.
Built and operated a research→production ML platform (Azure, Databricks, Spark, MLflow, SQL) with 100% uptime in 2024. 10k+ equities/day, ~500 features/stock, point-in-time data, lineage, automated ingestion, validation, and monitoring. Fully automated trading model pipelines; live strategies Sharpe 1–2 used by multiple PMs. Data quality & risk: rules engine, C2ST drift, SHAP, AUC tracking, alerts, auto-recovery. Research tooling: CV + walk-forward backtesting, randomization tests, feature importance, loss-function design, denoising autoencoder imputation. Led 4 engineers/researchers; enabled 15 PMs/researchers with shared quant library + data access layer. Research→prod <1 week; 20+ daily jobs orchestrated via CI/CD and dashboards.
The Certificate in Quantitative Finance (CQF) Financial Engineering program is designed for in-depth training for individuals working in, or intending to move into Derivatives, Quantitative Trading, Model Validation, Risk Management, Insurance or IT. CQF offers alumni lifelong Learning with lectures, and in this context I've lectured on recent advanced in Machine Learning / Reinforcement Learning.
Working on machine learning and classical algorithm for large scale real-time data processing in radio astronomy.