Vuyo Bandile Ndlangisa

Recent graduate with a solid foundation in computer science, data analysis, and problem-solving, actively seeking an entry-level role to gain hands-on industry experience. Proficient in Python and analytical thinking, with a proven track record of academic and personal projects emphasizing data manipulation, automation, and logical problem-solving. Highly motivated and quick to learn, prepared to contribute effectively to real-world projects while continuously enhancing technical and professional skills. Committed to leveraging a strong educational background to drive impactful results in a dynamic work environment.

Book Penetration Prediction (Alefbet – Honours Research)

• Merged and cleaned six raw datasets (41k+ matters) using SAS and Excel; engineered 20+ behavioural predictors.
• Performed EDA R and Python to analyze class imbalance and feature distributions.
• Built decision tree and logistic regression models in SAS (weighted/unweighted).
• Weighted logistic regression improved minority‑class recall from ~5% to >70% while maintaining ROC AUC ~0.80.
• Identified MatterAgeDays, employment status, and industry as top penetration drivers.
• Provided data‑driven recommendations to optimize calling strategies and account prioritization.