Data Scientist specialising in machine learning, model validation, and interpretable decision systems
I build and evaluate machine learning models using Python and SQL, with a focus on reliable performance, explainability, and real-world decision support. My work spans feature engineering, model validation, SHAP-based interpretation, and building interactive dashboards that translate data into actionable insight.
What I Deliver
Model Performance That Holds Up
Robust cross-validation, feature engineering, and careful metric selection to ensure models perform beyond test accuracy.
Explainable Insights for Stakeholders
SHAP-based interpretation and structured reporting that make model decisions understandable to non-technical teams.
Data to Decision
Dashboards and analytical outputs that translate predictions into practical business or operational action.
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