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About Candidate
I’m a Statistics graduate with a strong foundation in data analysis, programming, and research. My experience includes a 6-month Data Science internship and 4 years as a Research Assistant, where I developed skills in Python, SQL, Power BI, and cloud tools. I’m passionate about turning data into insights and solutions, and I’m eager to contribute to a team where I can continue learning and applying my skills to real-world challenges.
Education
Completed a 12-month intensive Data Engineering program focused on end-to-end data pipeline development, cloud computing, and analytics. Worked on real-world projects using Python, SQL, Power BI, Git, and AWS. Gained practical skills in data cleaning, transformation, dashboard creation, and building cloud-based data solutions to support business decision-making.
Completed a 6-month Data Science Foundations course focused on statistical thinking, data analysis, and machine learning. Gained hands-on experience in Python programming, data wrangling, exploratory data analysis, and model building. The course emphasized real-world problem solving and critical thinking in data-driven contexts.
Completed a Bachelor of Science degree majoring in Statistics, with Mathematics and Applied Mathematics taken throughout all three years. Built strong analytical and problem-solving skills through coursework in probability theory, statistical inference, calculus, linear algebra, and mathematical modeling. Gained hands-on experience with statistical tools like SPSS, MATLAB, and Excel for data analysis and interpretation.
Experiences
As a Research Assistant at Stellenbosch University, I was responsible for data collection, quality control, and analysis using REDCap, SPSS, and Excel. I contributed to research projects by cleaning and processing data, performing statistical analyses, and assisting with survey design. Additionally, I helped prepare manuscripts for publication and participated in academic writing, ensuring data accuracy and integrity for research findings.
As a Data Science intern at ExploreAI Academy, I worked on data cleaning, exploratory analysis, and building basic models using Python and SQL. I supported the team in creating data visualizations with Power BI and participated in several projects involving data transformation. I gained hands-on experience in data wrangling, statistical analysis, and machine learning techniques, allowing me to apply theoretical knowledge to real-world datasets.
As a Research Assistant Intern, I contributed to data collection, cleaning, and analysis for academic projects. I worked with tools like SPSS, MATLAB, and Excel to organize and analyze large datasets, ensuring accuracy and consistency. I also assisted with literature reviews, survey design, and academic writing. This experience helped me develop strong analytical skills and an understanding of research methodologies.
Skills
Excel
SPSS
Statistical analysis
Python (Data Analysis, Machine Learning)
SQL (Data Querying)
Data Cleaning & Preprocessing
Data Visualization (Power BI)
Quality Control & Data Accuracy
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