Data Analyst · Kaduna, Nigeria
Data Analyst
Data Analyst uncovering patterns and insights in your dataset — turning raw spreadsheets and databases into dashboards and decisions people actually trust.
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About
I'm a Computer Science graduate from Kaduna State University with a passion for data analytics and solving real-world problems with data.
I enjoy taking raw, messy data and turning it into something meaningful — uncovering patterns, finding insights, and using those insights to support better decisions. For me, data isn't just about numbers; it's about understanding the story behind them.
My work and interests span data analysis, machine learning, natural language processing, and Python-based solutions. I'm particularly interested in exploring how data and modern technologies can be used to solve practical problems and create useful, impactful solutions.
I'm also a strong believer in learning by building. I'm constantly experimenting with new tools, working on projects, strengthening my technical skills, and sharing what I learn along the way.
I'm building my career at the intersection of data, technology, and problem-solving — continuously improving my ability to turn complex information into clear, actionable insights. Whether I'm analyzing a dataset, training a machine learning model, or learning a new technology, I'm driven by one question:
"What can we learn from the data, and what can we do with it?"
Welcome to my portfolio. Take a look around and explore some of the things I've been building.
Let's talk about your dataToolkit
Microsoft Excel
Modeling, pivot tables, cleanup at scale
SQL
Joins, window functions, query tuning
Power BI
DAX measures, live report design
Tableau
Interactive, stakeholder-ready dashboards
Python
pandas, NumPy for analysis & scripting
Data Visualization
Turning numbers into a clear story
Selected work
A look at 75,513 consumer complaints (2011–2020) — mapping resolution-quality gaps, product-level dispute rates and where "closed without relief" cases were quietly driving escalation.
SQL and Power BI on 57,502 customer records — sizing high-value segments, comparing campaign profitability, and ranking channels by engagement for a company relying too heavily on discounts.
SQL and Excel on 8,000 patients across 80K records — surfacing a 7.8% readmission rate, a $165M total claim cost with a $88M insurance gap, and the diagnoses and departments driving cancellations.
Get in touch
Open to data analyst roles, freelance dashboards, and anyone who wants a second opinion on what their numbers are actually saying.
Open to data analyst roles, freelance dashboards, and new collaborations.
Available now