About me
Economist | Data Scientist | Researcher
I am an economist and data scientist with a strong focus on applied econometrics, big data analytics, and machine learning for business and economic policy-relevant questions.
I am currently in the final phase of my MSc in Development Economics at the University of Göttingen, Germany, sponsored by the prestigious fully funded DAAD Scholarship. Here, I work at the intersection of development economics, agricultural economics, environmental economics and ML & econometrics.
In practice, I build and analyse large datasets from collection and cleaning through to causal inference, predictive modelling, and clear communication of results to both technical and non-technical audiences, using R, Python, SQL/BigQuery, Power BI and Stata.
With over four years of combined research and industry experience across academic institutions, a Canadian data science firm, and a multinational pharmaceutical company, I enjoy translating real-world economic and business problems into empirical questions that deliver rigorous, reproducible analysis that can genuinely inform decisions.
Research & professional interests
- Development economics: poverty, migration, rural & urban livelihoods, and labor markets
- Agricultural economics: trade, food standards, land use, food security and agricultural productivity
- Environmental economics: climate policy, carbon leakage, renewable energy, sustainable food systems
- Digital health analytics, business intelligence, business forecasting and customer analytics
- Applied econometrics, machine learning and geospatial analysis for policy evaluation
Technical skills
Languages & Software
Analytics & ML Methods
Visualisation & BI
Languages
My journey
How I got here
My path into economics and data science began in Nigeria, where studying economics at FUNAAB first showed me how empirical thinking could make sense of complex, real-world problems. That early fascination with turning messy data into clear answers never left me.
After graduating, I joined Novartis's Sub-Saharan Africa division as a data analyst, my first real test of applying quantitative methods in a high-stakes, fast-moving environment. Working across multiple countries on health and commercial data taught me that rigour matters, but so does the ability to communicate findings to people who need to act on them. It was also where I discovered how much I enjoyed building things: models, dashboards, workflows that actually get used.
That appetite for building led me to TNI Inc. in Canada, where I worked as a data scientist on donor analytics and machine learning projects for major non-profits. The work was technically demanding and practically grounded, predicting attrition, optimising campaigns, making sense of messy behavioural data at scale. It deepened my conviction that the most interesting problems sit at the boundary between economic reasoning and modern data tools.
That conviction is what brought me to Göttingen. The DAAD Scholarship gave me the opportunity to pursue an MSc in Development Economics, and to do it seriously, at a research institution where I could work on questions that genuinely matter: environmental economics and policy agricultural trade, carbon policy, migration, food security. As a research assistant across two chairs, I get to do both: contribute to academic publications and build the kind of rigorous, reproducible analysis I have always been drawn to.
I am still driven by the same question I started with, how do we extract something true and useful from data? The tools have grown, the contexts have changed, but that core curiosity has stayed constant.