NOLWAZI MNDEBELE
Data Science/Data Analytics
Johannesburg,GP
Summary
Aspiring Data Scientist with a strong foundation in machine learning, statistical analysis, and cloud-based model deployment. Proficient in Python, SQL, Power BI, and AWS, with hands-on experience building end-to-end data solutions—including a deep learning–based satellite imagery segmentation application. Passionate about applying data science to solve real-world problems and adept at collaborating with cross-functional teams to deliver impactful, data-driven outcomes. Eager to further deepen expertise and contribute to innovative research and analytics projects.
Overview
1
1
year of professional experience
1
1
Certification
2
2
Languages
Work History
Research Assistant -Data Analytics
Ezintsha
07.2025 - Current
- Data Management: Collect, clean, and organize qualitative and quantitative data from various sources, ensuring data accuracy, consistency, and integrity.
- Data Analysis: Employ statistical methods and analytical tools (Excel, Python, SQL, Power BI) to interpret datasets, identify trends, patterns, and anomalies.
- Research Support: Assist in designing research methodologies, conducting literature reviews, and staying updated on emerging research developments to support manuscript preparation.
- Reporting & Visualization: Develop clear, insightful reports, presentations, and dashboards to communicate findings and implications to researchers and stakeholders.
- Collaboration: Work closely with multidisciplinary teams—including programmers, data analysts, and research leads—to define research needs and develop data-driven solutions.
- Documentation: Create and maintain detailed documentation of data processes, analysis workflows, and methodologies for clarity and reproducibility.
Project-based Internship
Sand Technologies
09.2024 - 11.2024
- Collected, analyzed and interpreted large datasets to extract valuable insight.
- Cleaned, prepared, and analyzed large datasets.
- Conducted exploratory data analysis to identify patterns, trends, and anomalies.
- Utilized statistical techniques (e.g., regression, hypothesis testing) to assess relationships between variables.
- Utilized Python, SQL, and PowerBI to analyze large datasets, extract actionable insights, and present findings to key stakeholders.
- Collaborated with cross-functional teams to integrate data science solutions into business strategies and operational workflows.
- Developed and implement predictive models (machine learning algorithms) to solve complex business problems and enhance decision-making processes and evaluated model performance using appropriate metrics and refined as needed.
- Built Streamlit applications for model inference and visualizing results.
- Developed and trained deep learning models (U-Net, DeepLabV3, and ResUNet) for binary segmentation of satellite imagery.
- Implemented custom data generators, data augmentation, and class balancing techniques.
- Optimized the ResUNet model by fine-tuning the learning rate, achieving superior performance in IoU and Dice metrics.
- Built a Streamlit app for model inference and visualizing segmentation results.
- Utilized AWS S3 for data storage and model deployment, ensuring scalability and accessibility.
Education
Data Science -
Explore AI Academy
12.2024
Master of Science - undefined
University of the Witwatersrand
12.2021
Bachelor of Sciences Honours - undefined
University of Limpopo
12.2018
Bachelor of Science - undefined
University of Limpopo
12.2017
Skills
Analytical & Research Skills
Certification
AWS Cloud Practitioner
Timeline
Research Assistant -Data Analytics
Ezintsha
07.2025 - Current
Project-based Internship
Sand Technologies
09.2024 - 11.2024
Master of Science - undefined
University of the Witwatersrand
Bachelor of Sciences Honours - undefined
University of Limpopo
Bachelor of Science - undefined
University of Limpopo
Data Science -
Explore AI Academy