Cannibalization Effects in Retail Promotions
Applied ML and causal inference to identify and quantify promotion-driven cannibalization, improving forecast accuracy for retail pricing optimization.
Applied Data Scientist
I build ML systems that turn noisy data into business decisions.
Analytics & ML — MIT
Economics & Finance — University College Dublin
I work on applied machine learning and analytics problems to help shape better decisions. I enjoy turning messy data into models and experiments that help teams understand behavior, test ideas, and build AI-driven systems.
Applied ML and causal inference to identify and quantify promotion-driven cannibalization, improving forecast accuracy for retail pricing optimization.
Built a dynamic pricing tool enabling Adecco sales reps to price contracts and negotiate with client companies, with risk-sensitive intervals that improved margins.
Compared BERT, XGBoost, GPT, and Hierarchical Attention Networks for spoiler detection in movie reviews.
Deep learning project using CNN, RNN, and Transformers to identify news article sources.
Optimization project using Julia and Gurobi to design carbon-efficient diets.
LSTM networks and MediaPipe for real-time American Sign Language to text translation.
Predictive maintenance using ML to prescribe optimal decisions.
Master of Business Analytics (MBAn)
GPA: 5.0 / 5.0 · 2023 - 2024
Focus: Machine learning, AI, optimization, and advanced analytics
BSc Economics & Finance, First Class Honours
GPA: 3.93 / 4.20 · 2019 - 2023
Focus: Mathematics, statistics, and economics
Entrance Scholar · Ad Astra Academic Scholar · First Year Top of Class