SU

Success Umazayi

Data Nerd

GitHub LinkedIn Email

Data Analyst / Data Scientist

Hi, I’m Success — I turn raw data into insights that support smarter decisions.

I am a Computer Science student at the University of Ilorin and a data analyst with a growing interest in data science and machine learning. I currently work with Python, SQL, Excel, and Power BI to analyze data and build dashboards, while expanding my skills in predictive modeling and statistical analysis.

Based in Nigeria • Open to Remote Opportunities
Focus Data Analysis · Data Science · Machine Learning . Artificial Intelligence
Availability I’m currently open for internships, entry-level roles, and collaboration opportunities.
Resume Download Resume (PDF)

Latest copy with roles, impact, and skills.

Who am I?

I am a data analyst and data scientist who enjoys turning raw data into useful insights that support better decisions. I work with tools like Python, SQL, Pandas, Excel, and Power BI to clean data, analyze trends, and communicate findings clearly, while continuing to build hands-on experience in machine learning.

Superpower

Turning business questions into data-driven insights and analysis.

Toolbox

Programming

  • Python
  • SQL

Data Analysis

  • Pandas
  • Numpy
  • Jupyter

Visualization

  • Power BI
  • Excel
  • Matplotlib
  • Seaborn

Machine Learning

  • Scikit-learn
  • Statistical Modeling
  • Feature Engineering

Bio

My journey into data began with a strong curiosity about how numbers, patterns, and trends can explain real-world problems and guide smarter decisions. Since then, I have been building practical experience in data analysis through projects involving data cleaning, exploratory analysis, dashboard development, and data storytelling.

I currently work with Python, SQL, Excel, and Power BI to analyze datasets, uncover insights, and present findings in a clear and actionable way. Beyond analytics, I am actively growing into data science by learning predictive modeling, feature engineering, and model evaluation, with a long-term goal of becoming a machine learning engineer.

As a data analyst and aspiring machine learning engineer, I am especially interested in opportunities that allow me to solve meaningful problems, strengthen my technical foundation, and contribute to data-driven teams.

“Everything interesting hides in the residuals.”

Tech Stack

Languages
Python SQL C C++ HTML CSS
Frameworks & Tools
Pandas NumPy Matplotlib Seaborn SciPy Scikit-learn Jupyter Power BI Excel Streamlit

Projects and Experiences

Sorted by recency
2026

Malaria Diagnosis

Personal · Remote

  • Performed exploratory data analysis with ydata_profiling to surface data quality issues, patterns, and early diagnostic signals.
  • Cleaned and prepared the dataset with Pandas to improve consistency, usability, and model readiness.
  • Engineered predictive features that improved how the models captured relationships within the data.
  • Trained and evaluated Random Forest and XGBoost classifiers, both achieving over 90% accuracy and recall.
  • Optimized for recall to strengthen identification of likely malaria cases and reduce the risk of missed positives.
View on GitHub Live Demo
2026

Car price Analysis and Prediction

Personal · Remote

  • Analyzed vehicle pricing data with NumPy and Pandas to identify the factors most associated with price variation.
  • Conducted exploratory analysis with ydata_profiling to document trends, outliers, and feature behavior.
  • Built Power BI dashboards to communicate pricing patterns and key performance insights in a business-friendly format.
  • Developed and compared Linear Regression, Decision Tree, Random Forest, and XGBoost models for price prediction.
  • Deployed an interactive Streamlit application that allows users to generate car price estimates from input features.
View on GitHub Live Demo
2026

Data Analysis Capstone Project – Schull.io

ST@40 · Remote

  • Cleaned and transformed raw datasets in Python using Pandas to support accurate downstream analysis.
  • Conducted exploratory data analysis to uncover trends, patterns, and actionable observations.
  • Designed Power BI dashboards to present key metrics and improve stakeholder visibility into performance.
  • Communicated findings through structured reports and presentations tailored to non-technical audiences.
View on GitHub
2026

Amazon Sales Data Analysis Project

CodeAlpha Task · Remote

  • Analyzed Amazon sales data to identify monthly performance trends and revenue patterns.
  • Created visualizations that translated raw sales activity into clear, decision-oriented insights.
  • Delivered a dashboard highlighting key sales KPIs to support performance tracking and reporting.
View on GitHub
Certification

ST@40 Digital Skills Training Initiative — Data Analysis

Schull Technologies · Partnership with Seyi Tinubu

Certificate of Participation - Data Analysis
Certification

TechCrush 15-week Bootcamp Scholarship — Data Science

Accredited by the American Council of Training and Development, USA

TechCrush Certificate of Completion - Data Science

Metadata

Favorite chart

Ridgeline plots for multi-distribution stories.

Learning

Artificial Intelligence and Machine Learning. Also exploring Software Engineering.

Reading

“Python for Data Science” & “Statistics”.