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najeebullahii/README.md

Hi, I'm Najib

Data Analyst and Data Scientist based in Kaduna, Nigeria. I graduated with a degree in Electrical Engineering from Bayero University Kano, and somewhere along the way discovered that the part I enjoyed most was finding patterns in data and building things that solve real problems.

I build end-to-end data projects, from web scraping and SQL analysis to machine learning models and AI-powered applications. My recent work includes a natural language to SQL engine powered by Google Gemini and a causal inference decision tool built on DoWhy. I enjoy creating things that did not exist before and I actively look for problems that are worth solving properly.

What I Work With

Python · SQL · Excel · Machine Learning · Tableau · Power BI · Streamlit · Google Cloud Platform · AI Applications

Featured Projects

FinQuery — Natural Language Analytics for E-Commerce Built an AI-powered analytics app that removes the barrier between business users and data. Instead of waiting for a data analyst to write a query, anyone can just type a question and get an instant chart. Runs on 1.6 million rows of real e-commerce data across 9 database tables. Powered by Google Gemini and live on Streamlit. Live Demo

Strategic Oracle — Causal AI Decision Engine A data project that helps businesses stop wasting marketing budget. Instead of just asking "which customers subscribed?", it asks "did our outreach actually cause them to subscribe, or would they have anyway?" Built with Python and deployed as a live interactive app. Live Demo

Lagos Real Estate Intelligence Built an end-to-end data project to answer a simple question: where in Lagos should you actually invest in property? Scraped nearly 2,000 real listings using Python, cleaned the messy data across three rounds, and built an interactive Tableau dashboard revealing that Ibeju Lekki delivers 9.3% annual returns while Ikorodu delivers just 0.3% — a 30x gap in the same city.

Telco Customer Churn Prediction Built a tool that predicts customer departures for a telecom company. I tested three different types of math models to find the most reliable one, ultimately reaching an 84% success rate in identifying customers who might leave.

Diabetes Readmission Analysis Analysed 10 years of diabetic patient hospital records using MySQL and Tableau to identify the primary risk factors driving 30-day hospital readmissions.

Currently

Completing NYSC · Actively seeking remote data roles

Get in Touch

LinkedIn

Popular repositories Loading

  1. Strategic-Oracle__Causal-AI-Decision-Engine Strategic-Oracle__Causal-AI-Decision-Engine Public

    Causal inference project using DoWhy to isolate the true marketing lift of bank contact methods. Applies Propensity Score Stratification to remove selection bias from raw campaign data and delivers…

    Python 1

  2. Telco_Customer_Churn_Prediction Telco_Customer_Churn_Prediction Public

    In this project, I analyzed telecom customer data to understand why customers leave and built machine learning models to predict churn and guide retention efforts.

    Python

  3. Diabetes_Readmission_Analysis Diabetes_Readmission_Analysis Public

    Analysed 10 years of diabetic patient hospital records using MySQL and Tableau to identify the primary risk factors driving 30-day readmissions, age, diagnosis type, and discharge disposition.

  4. Lagos-real-estate-analysis Lagos-real-estate-analysis Public

    I Scraped and analyzed 1,993 Lagos properties using Python. Built an interactive Tableau dashboard to uncover pricing trends, location insights, and real estate investment opportunities across Lagos.

    Python

  5. FinQuery-Natural-Language-Analytics-Ecommerce FinQuery-Natural-Language-Analytics-Ecommerce Public

    A natural language analytics engine that converts plain English business questions into SQL and delivers instant insights from 1.6 million rows of real e-commerce data — powered by Google Gemini.

    Python

  6. najeebullahii najeebullahii Public