Gaopalelwe Tiroyabone

As a highly qualified professional with a robust educational background in computer science and statistics from North West University, I bring a solid foundation in both theoretical principles and practical applications. With 9 months of experience as an Operations Technical Supporter at North West University, I have honed my technical support skills and demonstrated a capacity for problem-solving in a dynamic environment.

My career advanced to a pivotal role at Coca-Cola Beverages Africa, where I served as a Business Intelligence and Data Analyst intern for 12 months. In this position, I applied my analytical acumen and technical expertise to derive actionable insights from data, contributing significantly to strategic decision-making within the organization.

My journey reflects a seamless integration of academic knowledge and hands-on experience, positioning me as a versatile candidate capable of bridging the gap between computer science, statistics, and practical applications in a corporate setting. I am enthusiastic about the opportunity to bring my skills and insights to a new professional challenge, making meaningful contributions to your team.

Business Intelligence and Data Analyst Intern:

•Extracting data from various sources, cleaning, and transforming it for analysis and visualization.
•Designing and creating interactive dashboards to visualize key performance indicators (KPIs) and support decision-making.
•Generating reports for business, providing insight into business performance
•Ensuring the accuracy and reliability of data through thorough testing and validation.
•Presenting findings and recommendations to both technical and non-technical audiences.

 

Computer Science and Statistics:

• Data Visualization – Microsoft Excel, Microsoft Power BI, SAS, R, Python, MATLAB.
• SAS – Statistical Analysis, Time Series Forecasting, Predictive Modelling, Visualization.
• R – Statistical Analysis, Time Series Forecasting, Predictive Modelling, Visualization.
• SQL – Oracle Databases, Microsoft SQL.
• Mathematical Statistics – Probability and Sampling Theory, Statistical Inference, Data Analytics, Linear Models, Time Series (Analysis of Dependent Data)
• Mathematics – Calculus (1, 2, 3, and 4), Linear algebra, Real Analysis, Mathematical Modelling and Vector Algebra.
• Computer Sciences – Databases & Advanced Databases, Operating Systems, Computer Networks, Artificial Intelligence, Data Structures and Algorithm, Object Oriented Programming.
• Programming – Java, C/C++, Python, SQL, SAS, R.
• Computer literacy – Microsoft Applications (Word, Excel, PowerPoint)