I am an applied data scientist with a PhD and over 20 years of experience applying machine learning and statistical modelling to large, noisy and incomplete datasets. Until 2026 I was a Senior Lecturer (equivalent to US Associate Professor) at Victoria University of Wellington, New Zealand, where I led international data-intensive research programmes, published over 100 peer-reviewed papers and supervised 18 postgraduate projects in machine learning, statistics and scientific computing. I'm now based in Athens, Greece, and moving into industry data science.
Key achievements:
- Built TensorFlow deep neural networks on 100,000-record datasets that outperformed kNN and decision-tree models, and developed a missing-data imputation strategy that raised usable data from 46% to 80% with minimal loss of accuracy (sole-author, peer-reviewed).
- Designed and maintained end-to-end Python pipelines for data ingestion, pre-processing, modelling, validation and uncertainty estimation.
- Built a portfolio of production-style projects: fraud and money-laundering detection, customer segmentation, time-series forecasting, A/B testing and battery prognostics (1.6 million observations), with models deployed as containerised REST APIs (FastAPI, Docker).
Core skills: Python (pandas, NumPy, scikit-learn, XGBoost, TensorFlow), classification, clustering, anomaly detection, forecasting, deep learning, feature engineering, model validation, Bayesian inference and experimental design. Currently adding PySpark and Databricks.
What I'm looking for: a hands-on data scientist or machine learning role where modelling is the core of the work, in areas such as fraud and risk, forecasting, customer analytics or applied research. I enjoy turning messy real-world data into models people can act on, and explaining the results clearly to non-technical audiences, which years of teaching have made a strength.
Location and eligibility: based in Athens (UTC+2/+3). UK, Australian and New Zealand citizen, with the right to work in Greece, the EU and the UK without sponsorship. Open to roles in Athens, and remote roles across Europe or EMEA.
