Immanuel Bayu

I am driven by the challenge of transforming unstructured noise into strategic foresight. My transition into Data Science is fueled by a deep-seated interest in how mathematical frameworks can decode complex market behaviors. Recently, I developed a Technical Skill Forecaster, a machine learning tool designed to predict industry hiring trends. By bypassing standard K-fold cross-validation in favor of a Walk-Forward Validation strategy, I ensured model integrity by eliminating temporal data leakage.

My approach balances the high-capacity learning of Gradient Boosted Regressors with the structural stability of ARIMA models. I am a firm believer in building models that are not just accurate, but mathematically robust and ethically grounded. I am now looking to apply my background in predictive modeling and automated data pipelines to help a forward-thinking team turn "what happened" into "what’s next".