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Joshua Opadoja

Data Analyst

Exploring what’s possible with data.

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About

Grounded in analysis, growing toward more.

Portrait of Joshua Opadoja

I'm interested in what happens when curiosity meets data.

I started with data analysis because I wanted to understand how information can be turned into something useful. I'm not just talking about reports and dashboards, but about better questions, clearer decisions, and eventually better systems and solutions.

The past year has been about building projects and exploring what's possible with data, using tools such as SQL, Excel, Power BI, and Python. It's been about learning how to think through problems and turn what I learn into something tangible.

I'm currently building my foundations across data analysis, statistics, machine learning, and computer science. Each gives me a different way of looking at problems: data helps me find patterns, statistics helps me reason about uncertainty, and programming gives me the ability to build beyond the analysis itself.

Ultimately, I want to create things that are useful, and I'm just getting started.

Skills & technologies

What I work with

Data & Analytics

Python

Core

Data analysis, automation, and building reproducible workflows.

SQL

Core

Querying, joining, and transforming relational data to extract meaningful insights.

Excel

Core

Data cleaning, analysis, modeling, and building practical business solutions.

Power BI

Core

Building interactive dashboards and reports that communicate data clearly.

Exploring

Statistics

Exploring

Strengthening understanding of probability, inference, and statistical modeling.

Data Science

Exploring

Exploring data science techniques to uncover patterns and build models.

Machine Learning

Exploring

Learning ML algorithms and applications to make data-driven predictions.

More to come

Exploring

Continuously learning new technologies and approaches as they emerge.

Projects

Selected work

A selection of problems I’ve explored through data.

Bank Customer Churn Analysis preview
Data Analysis & Predictive Modeling

Bank Customer Churn Analysis

Analyzed 10,000 bank customers to identify demographic and behavioural drivers of churn, validate key patterns statistically, and build a Random Forest model to predict customers at risk of leaving.

PythonPandasNumPyMatplotlibSeabornSciPyScikit-learn
New Zealand Vehicle Theft Analysis preview
Data Analysis & Crime Intelligence

New Zealand Vehicle Theft Analysis

Analyzed New Zealand vehicle theft data to uncover trends across time, vehicle types, and regions, identify high-risk patterns and regional disparities. The findings were translated into practical recommendations for targeted prevention.

Power BIDAXPower Query
Coming soon
Coming Soon

Operation Clearwater

A new project currently in development. More details will be shared when it's ready.

IN DEVELOPMENT
Writing

Notes & Ideas

Thoughts on data, technology, learning, and building.

The first note is taking shape.

“Creativity is intelligence having fun.”