I'm a data analyst from Niger. I like digging into messy datasets to understand what's actually going on, and building small tools — some of them AI-based — around problems I see at home.

I'm currently open to new opportunities — feel free to reach out.

• 📈 Statys — A multi-tenant platform that lets an analyst explore a dataset without writing any code. You drop in a CSV or Excel file, and it walks through each variable — univariate and bivariate analyses, with the right statistical test picked for you — then exports the whole thing as a PDF report. Node.js on the front, FastAPI on the back.
• 💬 Niger Fintech Reviews — I scraped the Google Play reviews of Niger's mobile money and banking apps to see what people actually complain about. After cleaning them up, I tagged the recurring themes, ran sentiment on them, and put it all in a dashboard with a short write-up of what it means for the apps.
• 🗳️ Niger 2020 Election Analysis — A close look at the first round of Niger's December 2020 presidential election, commune by commune — all 266 of them. I turned the raw CENI results into clean datasets, explored them in a notebook, and built a single-file HTML dashboard where you can read the winner and turnout off a map, filter by region, and search the table.
• 🌊 Niger Flood Early Warning — A small early-warning system for floods in Niger. It scores each department's risk from open climate data (rainfall, vegetation via NDVI) and the flood impacts OCHA has recorded over the years.
• 💳 Mobile Money Fraud Detection — Catching fraudulent mobile money transactions in the MoMTSim dataset, from cleaning the data in Python through the SQL queries to a dashboard built with Tableau and Chart.js.
• 📄 ATS — AI Resume Screener — CV screening without the tedious part: you paste a job description, the app reads a Google Drive folder of resumes and ranks candidates by how well they fit, using Gemini. No database, nothing stored — just TypeScript.
• 🍽️ Niamey Restaurants Analysis — If you wanted to open a restaurant in Niamey, where would you put it, and what kind? I scraped ~490 places off Google Maps and dug in: cleaning with Python and DuckDB, a few statistical tests, geospatial clustering on maps, and a scoring model to rank neighborhoods against each other.
• 🪑 Market Scanner Niger — Gaskiyar Kaya 🇳🇪 — a little AI tool that judges the quality of second-hand furniture from a photo, so buyers in Niger have a better idea of what they're paying for.
• 🛒 Customer Behavior Analysis — Digging through 3,900 shopping records to understand what drives customer behaviour, from exploring the data in Python and PostgreSQL to a Power BI dashboard and a written report on segments, revenue, discounts, and loyalty.
• 📡 MTN Churn Analysis — Why do MTN Nigeria customers leave? I looked at 974 records (496 customers) with Python, PostgreSQL, and Tableau. Churn lands at 29.2%, and the report points to the segments worth focusing retention on.
• 🌱 More projects on the way.

Focus areas: Data Analysis · Data Visualization · SQL & NoSQL Databases · Data Wrangling · Web Scraping · Geospatial Analysis · Statistical Testing

• 💼 LinkedIn: linkedin.com/in/mohassane

_{💬 Open to opportunities in data analysis.}