Samuel | Portfolio

About Me

Hello! I'm Samuel Oyebamiji, a passionate and results-driven Data Scientist with hands-on experience in solving real-world problems through data. I specialize in extracting insights from complex datasets, building predictive models, and developing data-driven solutions that drive business growth. With expertise in Python, SQL, Power BI, and machine learning frameworks, I've worked on multiple projects ranging from predictive analytics and fraud detection to market basket analysis and crop yield forecasting. My ability to transform raw data into actionable insights helps businesses optimize operations, improve decision-making, and achieve measurable success. Beyond technical skills, I bring a strong analytical mindset and a problem-solving approach to every project. Whether it's forecasting stock trends, detecting anomalies in financial transactions, or building NLP models to track political campaign promises, I thrive on turning data into meaningful impact. I'm always eager to collaborate on exciting projects, explore innovative data solutions, and share knowledge with the data community.

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My Services

Machine Learning & AI

Building predictive models using machine learning algorithms to solve real-world problems.

Data Analysis & Insights

Analyzing complex datasets to uncover trends, patterns, and actionable business insights.

Data Visualization & Storytelling

Creating compelling visualizations and dashboards using Power BI, Python, and SQL.

Natural Language Processing (NLP)

Developing AI models to process and analyze text data, including sentiment analysis and chatbots.

Big Data & Cloud Computing

Handling large-scale datasets with cloud platforms like Google BigQuery and AWS.

End-to-End Data Science Solutions

Designing, developing, and deploying complete data science solutions tailored to business needs.

Projects

Car Sales Dashboard

Analyzed car sales trends by body style, color, and company to optimize inventory and pricing strategies using Power BI.

Sales Overview Dashboard

The West leads in sales and profit growth, while Central and South face profit drops. Focus on improving weaker regions and expanding strong ones.

Customer Churn Prediction

Built a machine learning model using Logistic Regression, Random Forest, and XGBoost to predict customer churn. Identified key churn factors and developed an interactive dashboard for insights and retention strategies.

Market Basket Analysis for Nigerian Retailers

Used association rule mining (Apriori, FP-Growth) to identify frequently bought-together items.

Crop Yield Prediction for Nigerian Farmers

Developed a regression model (Random Forest, XGBoost, LSTMs) to predict crop yields.

Loan Default Risk Prediction

Built a model to predict loan default risk using classification techniques (Logistic Regression, Random Forest, XGBoost) to assist financial institutions.

Movie Recommendation System

A recommendation system built using SQL and Python to suggest movies based on user preferences.

Fraud Detection in Mobile Money Transactions

Built a classification model using Random Forest, XGBoost, and Isolation Forest to detect fraudulent transactions.

Hi, There

I'm Samuel Oyebamiji