Nkosingiphile Radebe

I’m a data-driven analyst with experience analysing operational, customer, and incident data to improve performance, strengthen data governance, and support compliance within regulated environments. I monitor KPIs and track SLA adherence, using reporting to spot operational risks and service-delivery issues early. I’m comfortable working across multiple systems to maintain data accuracy, consistency, and compliance with internal controls.

In my role as a Junior Data Analyst at The Unlimited, I clean and validate large operational datasets and reconcile data across systems to ensure reliability for reporting. I build Power BI dashboards to monitor KPIs, SLA adherence, and operational performance trends, and I analyse claims and customer service data to identify process inefficiencies, delays, and risk indicators. I also support decision-making by transforming data into actionable insights, while contributing to improving data quality and governance.

Alongside my work, I strengthen my technical edge through data science projects and training. I built a customer review sentiment analysis pipeline using NLP and spaCy on 34,000+ Amazon reviews, and I developed a housing price prediction model using PyTorch with LSTM and GRU networks. I’ve also created a data cleaning and automation toolkit in Python to reduce manual preparation time, and I designed a retention dashboard in Power BI connected directly to SQL Server using DAX for real-time KPIs.