Quantitative Data Scientist (Independent Research)
Prince A. Audu University Independent Research
Dec 2024 - Current (1 year 2 months)
Modelled a deep learning (LSTM/GRU) neural network on a fintech transaction dataset of over 4,000 users, achieving 90%+ prediction accuracy for churn detection, and reducing customer attrition risk by 12%. Utilized proprietary customer spend data to identify 15+ distinct spending patterns, leading to a novel customer segmentation algorithm that improved targeted marketing efficiency by 20% and increased revenue by 5%.