End-to-end analytics pipeline on 16,000+ rows of Irish CPI data (2020–2024). Four predictive models benchmarked to quantify inflation's real impact on low-income families.

• Built Python pipeline to clean, filter, and aggregate CPI data across housing, energy, transport, and food sectors
• Programmed and evaluated ARIMA, Linear Regression, Random Forest, and Neural Network — ARIMA identified as most accurate for short-term forecasting
• Developed sector-specific dashboards for non-technical stakeholders

Hybrid prediction system combining regression models with a VGG13 convolutional deep learning architecture to decode complex airline pricing dynamics.

• Combined VGG13 CNN with regression to analyse booking windows, seasonality, and demand fluctuations
• Managed full ML lifecycle — data ingestion, feature engineering, model training, validation, and documentation
• AI-based models outperform regression for dynamic pricing; applicable to consumer cost-optimisation