Muphulusi Dzivhani is a skilled Problem Analyst at the South African Revenue Service (SARS), with a strong passion for data science, data analytics, and cybersecurity. Aspiring to achieve distinction as a successful Data Scientist, Muphulusi's career is marked by significant accomplishments, including an honors degree in Mathematics, accreditation as a Certified Ethical Hacker, and a Data Science certification from Explore AI Academy.

Currently, Muphulusi is pursuing a Master's in IT Data Science, with a research project titled "Enhancing Financial Fraud Detection through Big Data Analytics and Machine Learning Techniques." This research aims to develop a dynamic and scalable framework for improving the accuracy and timeliness of fraud detection using advanced big data infrastructure and machine learning models. It will also support her work in IT audit by identifying PCI fraud detection and helping to create policies within the organization to prevent such incidents.

In the role at SARS, Muphulusi utilizes tools such as Symantec DLP, QRadar, Active Directory, QlikView, Remedy, SQL, Power BI, Excel, and Python to analyze data, prevent unauthorized access, and create audit reports and policies across areas like Company Income Tax, Card Payments Fraud Detection, VAT, and Personal Income Tax.

Muphulusi is dedicated to continuous learning and skill development, striving to stay at the forefront of data science and cybersecurity.

Get in Touch Let's Work Together on Your Next Big Project