
Worked on the DataBytes-Organisation/DiscountMate_new repository to deliver a data cleaning pipeline and initial price forecasting models over a two-month period. Developed SQL scripts and Python workflows to clean and preprocess Coles and Woolworths datasets, addressing duplicate entries, category filtering, and missing data. Expanded synthetic data resources to support robust testing and demonstration scenarios. Implemented LSTM and ARIMA time series models using Keras, TensorFlow, and Statsmodels, establishing a reproducible training and evaluation workflow for price prediction. The work emphasized data reliability, analytics readiness, and rapid experimentation, with a focus on maintainable, traceable code and reproducible results throughout the project.
May 2025 monthly summary for DataBytes-Organisation/DiscountMate_new. Delivered initial price forecasting capability by adding two time-series models (LSTM and ARIMA) using synthetic transaction data. Focused on data preprocessing, model implementation, and establishing an initial training setup to enable rapid experimentation and iteration.
May 2025 monthly summary for DataBytes-Organisation/DiscountMate_new. Delivered initial price forecasting capability by adding two time-series models (LSTM and ARIMA) using synthetic transaction data. Focused on data preprocessing, model implementation, and establishing an initial training setup to enable rapid experimentation and iteration.
April 2025 performance summary for DataBytes-Organisation/DiscountMate_new: Delivered data quality and testing capabilities by implementing a dedicated data cleaning pipeline for Coles/Woolworths data and expanding synthetic testing data resources. The work emphasizes business value through improved data reliability and accelerated analytics readiness.
April 2025 performance summary for DataBytes-Organisation/DiscountMate_new: Delivered data quality and testing capabilities by implementing a dedicated data cleaning pipeline for Coles/Woolworths data and expanding synthetic testing data resources. The work emphasizes business value through improved data reliability and accelerated analytics readiness.

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