Ibrahim Ismail Busayo

Data Science

https://talent.gravityer.com/ibrahim-ismail-busayo

Key Strengths

Strong foundational knowledge in machine learning algorithms (XGBoost, Random Forest, Logistic Regression) and their application to real-world problems.
Demonstrated ability to build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, hyperparameter tuning, and deployment (Streamlit).
Experience with addressing common ML challenges such as class imbalance (SMOTE, StratifiedKFold) and model evaluation using appropriate metrics (AUC-ROC, Recall, R², MAE).
Proficiency in Python and key data science libraries (Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn).
Practical experience in data analysis and visualization, as evidenced by the NBS internship and project work with Power BI.
Exposure to NLP techniques (TF-IDF) and geospatial data analysis (QGIS certification).
Strong problem-solving and analytical thinking skills, crucial for a Data Scientist role.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate shows a strong drive for continuous learning and self-improvement, evidenced by pursuing dual degrees, multiple certifications (Data Science, QGIS, Database Management), and participation in competitive programs (HNG Internship, 3MTT). Their involvement in diverse projects, from fraud detection to fake news classification and geospatial analysis, indicates a broad interest and adaptability. The achievements in the 3MTT Knowledge Showcase and HNG Internship highlight a proactive and competitive spirit, which aligns well with a dynamic, results-oriented culture.

Soft Skills & Operational Fit

The candidate demonstrates strong analytical thinking, problem-solving, and adaptability through their project work and diverse academic background. Their experience in team collaboration (HNG Internship, 3MTT Capstone projects) and documentation skills (Django REST APIs, project reports) indicate a good operational fit. The ability to coordinate and manage tasks from their current role also suggests organizational capabilities.

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About

Data Scientist and Backend Developer with hands-on experience delivering end-to-end machine learning pipelines, RESTful APIs, and data-driven applications. Contributed analytical work at the National Bureau of Statistics supporting Nigeria's national trade reporting on oil and non-oil import/export data. Proficient in Python, Scikit-learn, XGBoost, Django, and Streamlit. HNG Internship X Finalist (Top 300 of 22,000). Winner of the 3MTT Knowledge Showcase and Abuja regional representative at the 3MTT Impact Summit. Certified in Data Science (3MTT/NITDA), Geospatial Analysis (QGIS — Energy Access), and Database Management. Seeking to apply strong statistical, geospatial, and ML skills to high-impact data science challenges.

Top Skills

PythonScikit LearnXgboostDjangoDocumentation

Experience

National Bureau of Statistics (NBS), Nigeria

Industrial Training Intern — Data & Tech

March 1, 2025 – January 1, 2026

India

Zuri HNG Internship

Backend Developer Intern (Remote)

September 1, 2023 – October 1, 2023

India

Federal Ministry of Labour and Employment

Technical Officer

January 1, 2022 – Present

India

Federal Ministry of Labour and Employment

Assistant Trade Testing Officer

January 1, 2019 – December 1, 2021

India

Projects

Credit Card Fraud Detection System

June 17, 2026 – Present

Built an ML-powered web app to detect fraudulent transactions using Random Forest and Logistic Regression on 284,000+ records with 0.17% fraud rate Achieved 99.9% accuracy, 0.9999 AUC-ROC, and 90% recall; addressed class imbalance using StratifiedKFold cross-validation and GridSearchCV Deployed interactive Streamlit interface enabling CSV/Excel upload with fraud predictions, probability scores, and downloadable results

View Project

Insurance Premium Prediction

June 17, 2026 – Present

Applied advanced feature engineering: log transforms, interaction terms (age × health score, income × credit score), quantile binning, and variance thresholding Identified and corrected hidden placeholder values in credit score data; compared 3 regression models with full hyperparameter tuning — 3MTT Capstone Project

View Project

Fake News Detection App

June 17, 2026 – Present

Won the 3MTT Knowledge Showcase with this NLP-powered classifier using Logistic Regression + TF-IDF bigram vectorization; achieved 99% accuracy on test data Trained on Kaggle Fake and Real News Dataset; deployed as a live Streamlit application classifying news headlines as Real or Fake in real time

View Project

Delivery Delay Prediction — SwiftChain Analytics

June 17, 2026 – Present

Built multiclass classification pipeline predicting delivery status (Late/On-Time/Early); engineered shipping duration features and applied SMOTE for class imbalance Compared Logistic Regression, Random Forest, and XGBoost with GridSearchCV tuning; documented results and actionable recommendations — 3MTT Capstone

View Project

Employee Burnout Prediction

June 17, 2026 – Present

Built regression model predicting employee burnout rate; achieved R² = 0.90, MAE = 0.0485 using XGBoost after comparing Linear Regression and Random Forest Applied RandomizedSearchCV (100 iterations, 3-fold CV); identified Mental Fatigue Score, Tenure, and Resource Allocation as top predictors — 3MTT Capstone Project

View Project

Certifications

Data Science

3MTT / NITDA

December 1, 2025 – Present

QGIS for Energy Access: Geospatial Data Management, Analysis & Modelling

QGIS / Kartoza / Energy Commission of Nigeria

October 1, 2025 – Present

Database Management (3-month programme)

Mentors Without Borders (MWB) / FSI

February 1, 2024 – Present

Backend Developer — HNG Internship X Finalist

HNG Internship (Zuri)

November 1, 2023 – Present

Python Programming Foundations

Udacity

May 1, 2022 – Present

Key Strengths

Strong foundational knowledge in machine learning algorithms (XGBoost, Random Forest, Logistic Regression) and their application to real-world problems.
Demonstrated ability to build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, hyperparameter tuning, and deployment (Streamlit).
Experience with addressing common ML challenges such as class imbalance (SMOTE, StratifiedKFold) and model evaluation using appropriate metrics (AUC-ROC, Recall, R², MAE).
Proficiency in Python and key data science libraries (Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn).
Practical experience in data analysis and visualization, as evidenced by the NBS internship and project work with Power BI.
Exposure to NLP techniques (TF-IDF) and geospatial data analysis (QGIS certification).
Strong problem-solving and analytical thinking skills, crucial for a Data Scientist role.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Ibrahim Ismail Busayo

Key Strengths

Cultural & Operational Fit

About

Top Skills

Skills

Education

Experience

Projects

Certifications

Key Strengths

Cultural & Operational Fit