DATA ANALYST · STATISTICIAN · Problem SoLver

I turn data into insights you can understand, trust, and act on.

Hi, I'm John, a data analyst with a background in statistics. I help businesses, students, and researchers make sense of data through statistical analysis, data visualization, predictive modeling, and forecasting.

I combine statistical thinking with practical data analytics to answer questions, uncover patterns, and turn raw data into useful information.

Python · SQL · Power BI · Figma · Statistics · Forecasting

Work With Me

Explore My Work

Data is everywhere, Good Analysis isn't

Having data is one thing.

Knowing what to do with it is another.

A spreadsheet can contain thousands of rows and still leave you wondering:

What does this mean?

What is driving the result?

Is this relationship actually significant?

What is likely to happen next?

What decision should I make from this?

That's the kind of problem I enjoy solving.

I take complex or messy data, ask the right questions, apply appropriate analytical and statistical methods, and turn the results into insights that people can actually understand and use.

My approach is simple:

Ask the right question → Analyze the right data → Use the right method → Explain the result → Take action

WHAT I DO

I help turn data into answers

Data Analysis & Exploration

I help transform raw or messy datasets into structured information that can be explored and understood. I can help with: Data cleaning · Data preparation · Exploratory data analysis · Descriptive statistics · Correlation analysis · Trend analysis · Outlier investigation Tools: Excel · Python · SQL

Data Analysis & Exploration

Statistical Analysis

When a question requires more than descriptive charts, I use statistical methods to help determine what the data actually supports. Areas include: Hypothesis testing · Confidence intervals · Statistical inference · t-tests · Chi-square tests · Correlation · Non-parametric methods The focus is not simply producing a p-value. It's understanding what the statistical evidence means.

Statistical Analysis

Regression, ANOVA & Econometrics

I analyze relationships between variables and investigate factors that may influence an outcome. Areas include: Linear regression · Multiple regression · Regression diagnostics · ANOVA · Correlation · Econometric analysis · Model interpretation The goal is to move from: "These variables are related." to: "Here's what the relationship tells us and how confidently we can interpret it."

Regression, ANOVA & Econometrics

Data Visualization & Business Intelligence

Good analysis becomes more useful when people can understand it quickly. I create visualizations and dashboards that turn complex datasets into clear information. Tools: Power BI · Figma · Python · SQL From KPI dashboards to exploratory visualizations, I focus on presenting information around the questions that matter.

Data Visualization & Business Intelligence

Time Series & Forecasting

Historical data can contain valuable information about what comes next. I work with time-series data to investigate: Trend · Seasonality · Patterns · Relationships · Forecasts Methods can include: ARIMA · SARIMA · Time-series decomposition · Forecast evaluation · Predictive modeling

Time Series & Forecasting

WHO I WORK WITH

Business Owners & Teams

Your business is generating data. Let's make it useful. I can help you understand sales, customers, performance, trends, and other business metrics. Examples: Sales analysis · Customer analysis · KPI dashboards · Performance reporting · Trend analysis · Forecasting

Business Owners & Teams

Let's Discuss Yout Business Data

Students

Don't just produce statistical output. Understand it. If you're working with a dataset for a project, dissertation, thesis, or research assignment, I can provide analytical support to help you understand your data and interpret your results. Support can include: Data preparation · Statistical analysis · Regression · ANOVA · Hypothesis testing · Visualization · Interpretation

Students

Discuss Your Dataset

Researchers

Turn research data into meaningful evidence. I help researchers analyze quantitative data and communicate statistical findings clearly. From selecting appropriate methods to interpreting results, the focus is on producing analysis that is statistically sound and understandable.

Researchers

Discuss Your Resaerch

TOOLS & STATISTICAL EXPERTISE

Technical range, applied with judgment.

Tools matter when they make the work more reliable, repeatable, and accessible to the people who need to act on it.

Excel, Python & SQL

Data preparation, queries, reproducible analysis, and modelling.

Power BI & Figma

Decision-friendly dashboards and stakeholder-ready visual systems.

Inference Methods

Hypothesis testing, regression analysis, ANOVA, and econometrics.

Time-Series Analysis

Forecasting and predictive modelling for better planning horizons.

WORKING PROCESS

A clear process makes the analysis stronger.

Ask

Before touching the dataset, I want to understand what we're actually trying to discover.

Understand

Where did the data come from? What does each variable represent? What problems might exist?

Method

Not every problem requires machine learning. Not every question requires a complicated statistical model.

The method should fit the question, data, and assumptions

Question Results

A statistically significant result isn't automatically an important result.

A correlation isn't automatically causation.

A model isn't automatically useful because it produces a prediction.

Good analysis requires critical thinking..

Communicate

The final analysis should make sense to the person using it—not only to the person who performed it.

Act

Connect insights to an action someone can own.

The best analysis answers:

"So what?"

And ideally:

"What should we do next?"

SELECTED WORK

Evidence designed to be used, not just presented.

01 / DATA CLEANING & PRE-PROCESSING

An end-to-end database overhaul for a US grocery chain

By utilizing PostgreSQL to correct systemic bugs, parse messy string formats, and impute missing values, this project transformed a corrupted database into a standardized, analysis-ready foundation for dynamic pricing strategies.

02 / TIME-SERIES FORECASTING USING DEEP LEARNING AND TRADITIONAL MODELS FOR NGX

A hybrid forecasting framework for the volatile Nigerian Exchange.

By pairing SARIMA for linear trends with a deep learning RNN to correct non-linear market shocks, this model bridges statistical rigor and AI—delivering an exceptional 0.47% error rate rather than a standalone black-box prediction..

03 / SATISTICAL ANALYSIS (ANOVA)

A rigorous statistical analysis designed to optimize agricultural output

By executing a comprehensive One-Way ANOVA in R and enforcing strict baseline assumption testing, this project mathematically isolated the exact fertilizer brand driving maximum crop yield—eliminating operational guesswork for agricultural stakeholders.

04 / DATA EXPLORATION

A Python-driven exploratory data analysis of a century of Nobel Prize history

By leveraging pandas and seaborn for temporal aggregation and proportional analysis, this project uncovers demographic trends and visually maps historical shifts in global representation over time.

View all on GitHub

LET’S MAKE THE DATA USEFUL

Have a question worth answering?

Tell me what you’re trying to understand. We’ll start with the decision, then build the analysis around it.

TEACHING & LEADERSHIP

Good analysis is also good explanation.

Alongside client work, I support students and researchers with structured statistical thinking—helping them understand the method, not just receive an output.

The goal: stronger questions, clearer reasoning, and work that stands up to review.

WHY WORK WITH ME

Decision first

Every project begins with the outcome you need to make possible.

Methodical

The method fits the data, the question, and the level of certainty required.

Clear communication

You receive an explanation and an action—not an unexplained chart or model.