Ojonugwa Wada

Hi, I'm Ojonugwa Wada

I am an innovation and data science specialist currently completing my MSc in Data Science at the University of Roehampton, London. Growing up on a small farm in rural Nigeria, I witnessed firsthand how flooding, financial exclusion, and limited infrastructure can hold communities back. Those experiences shaped my commitment to developing practical, data-driven solutions at the intersection of artificial intelligence, financial inclusion, and agroecological systems.

My work spans cross-sector initiatives integrating fintech and agritech, designing decision intelligence systems, and contributing to sustainable development projects across Africa. I founded Living Festival Storyworld, an AI-enabled cultural platform that explores African and diaspora narratives. I also lead research collaborations, including a formal partnership with CEPODRA Civil Association in Peru, where we co-develop data systems that strengthen local farming and disaster resilience.

Whether building machine learning models, analytics dashboards, or predictive frameworks, my approach prioritises human dignity, community resilience, and long-term social impact. For me, technology must serve people first.

Skills

● Data analysis, exploratory analysis and insight communication97%
● Statistical modelling, hypothesis testing and experimental design95%
● Machine learning development, validation and performance evaluation96%
● Feature engineering, data preprocessing and pipeline design95%
● Decision intelligence systems and applied AI for real-world use cases93%
● Dashboard development and data storytelling (Streamlit, Power BI)96%
● Research design, field data collection and impact reporting95%
● Stakeholder engagement, cross-sector collaboration and project delivery93%
● Financial modelling and fintech integration92%
● AgriTech systems, sustainability analytics and rural innovation94%

Tools / Software

● Python (Pandas, NumPy, Scikit-learn)98%
● Streamlit / Plotly / Matplotlib96%
● SQL and database management95%
● Git / GitHub97%
● Jupyter Notebook / VS Code96%
● Power BI / Excel (Advanced)92%
● Tableau90%
● Google Colab / JupyterLab94%
● Docker (basics)85%
● Overleaf (LaTeX) / Research writing workflow90%

Work Sample

An interactive Streamlit dashboard for predicting student performance using behavioural and lifestyle indicators. The system enables dynamic model comparison, trend analysis, and scenario simulation.

▶ View Project
📍 London, United Kingdom