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Data Scientist. Machine Learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Crop-Yield-Prediction
October 8, 2025 – October 8, 2025
Crop-Yield-Prediction — GitHub repository
View ProjectNigeria-Food-Outlook
September 17, 2025 – September 17, 2025
Nigeria-Food-Outlook — GitHub repository
View ProjectDataAnalytics-Assessment
May 17, 2025 – May 19, 2025
DataAnalytics-Assessment — GitHub repository
View ProjectJust_SQL
November 7, 2024 – November 7, 2024
This repository contains the SQL (PostgreSQL) code I wrote as part of my SQL learning journey
View ProjectMock-Interview-for-Data-Science
October 17, 2024 – October 17, 2024
This repository for solving data science related technical questions using Python programming language
View ProjectForecasting-Nigeria-Inflation-With-Machine-Learning
September 30, 2024 – September 22, 2025
Forecasting-Nigeria-Inflation-With-Machine-Learning — GitHub repository
View Projectalx-frontend-javascript
January 26, 2023 – January 26, 2023
The repository is for ALX Frontend Specialization JavaScript Projects
View ProjectEnglish-Premier-League-Project
January 14, 2022 – March 1, 2022
This is a project I did exposing me into the world of Sport Analytics. Football Analytics precisely. In this project I tried to predict the winner of an English Premier League Match; whether the Home Team or the Away Team using Random Forest Classifier. I also tried to gain insights from the given data. The data was gotten from footbal-data.co.uk
View ProjectCultural Fit Analysis
The candidate shows initiative through several personal projects, indicating a self-starter attitude. The diversity of projects (food outlook, inflation forecasting, sports analytics, crop yield prediction) suggests a broad interest in applying data science to different domains. However, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, limiting insight into collaboration, problem-solving approaches, or communication style.