I build forecasting models, ML pipelines, and data-driven tools that translate complex datasets into decisions businesses can act on.
End-to-end forecasting analysis using classical and ML approaches to model real-world book sales demand.
Demand forecasting for The Alchemist and The Very Hungry Caterpillar using SARIMA, XGBoost, LSTM, and hybrid model architectures. Evaluated across MAPE, MAE, and RMSE with residual diagnostics.
A decade in financial systems and analytics gave me an instinct for data quality and what business decisions actually hinge on. I'm now completing a Level 7 in Data Science, Machine Learning & AI at the University of Cambridge — applying that experience to predictive modelling and forecasting.
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