AI/ML Engineer · Data Scientist · Data Analyst Based in Ibadan, Nigeria · B.Tech Statistics, LAUTECH (2024)
I build machine learning and AI systems, and I analyse data to answer business questions. My work runs from SQL and dashboards to deep learning models, retrieval-augmented chatbots and fine-tuned language models. I like projects where the result is something a person can open, use and understand, whether that is a dashboard, a Streamlit app or a deployed model.
| Area | What it covers | Tools |
|---|---|---|
| AI / ML Engineering | LLM agents, RAG chatbots, LoRA fine-tuning, deep learning for text and images | Python, PyTorch, TensorFlow, Keras, LangGraph, Gensim |
| Data Science | Regression, clustering, classification, forecasting, panel data models | Python, scikit-learn, Jupyter, Streamlit, Render, VS Code |
| Data Analytics | Cleaning, SQL analysis, KPI dashboards, guest and customer insights | Excel, Power BI, SQL, Python |
| Project | What it does |
|---|---|
| react-agent-langgraph | A ReAct-style LLM agent built with LangGraph |
| health_rag_bot | A retrieval-augmented chatbot for health questions |
| tinyllama-lora-ai-engineering | Fine-tuning TinyLlama with LoRA |
| Multi-Task Learning with BERT on SICK | One BERT model trained on several tasks from the SICK dataset, in PyTorch |
| Yoruba-English Translation Model | A sequence-to-sequence model translating between Yoruba and English |
| RNN vs GRU vs LSTM for Text Generation | Side-by-side comparison of three recurrent architectures |
| Word2Vec Analysis of ChatGPT Reviews | Word embeddings on ChatGPT Google Play reviews, using Gensim and Keras |
| trashnet-cnn-classifier | A CNN that classifies waste images |
| Dry Beans Classification | Deep learning classifier for dry bean types, in TensorFlow |
| DSN_Hackathon | Hackathon project |
| Project | What it does |
|---|---|
| NaijaFoodPrice Intelligence | Analysis and forecasting of Nigerian food prices |
| student-segmentation-app | An app that groups students into segments |
| Student Segmentation with Hierarchical Clustering | Hierarchical clustering of student data |
| Wholesale Customer Segmentation with DBSCAN | Density-based clustering of wholesale customers |
| Gene Expression Clustering | PCA, K-Means and t-SNE on gene expression data |
| Bank Marketing with Boosting Models | Boosting models on the bank marketing dataset |
| Food Delivery Time Prediction | Multiple linear regression to predict delivery time |
| Ridge Regression on Crypto Sentiment | Ridge regression for crypto sentiment prediction |
| Clustered Robust Random Effects | Panel data model on life expectancy across countries |
| Student Performance Prediction | Logistic regression and decision tree models to flag students at risk of failing, with and without earlier grades as an early-warning test |
| Project | What it does | Tools |
|---|---|---|
| Hotel Guest Experience Analysis | Dashboard on 1,948 hotel guests covering satisfaction, purpose of visit and discovery source | Excel |
| Transaction Intelligence Analysis | SQL analysis of transaction data | SQL |
| Global Store Sales Performance | Dashboard on 9,994 order lines covering sales, profit, cost and quantity by region, state, category, ship mode and sales team | Power BI |
| Bank Customer Churn Analysis | Churn analysis of 9,997 customers by gender, country, age, balance, salary and number of products, using engineered customer groups | Excel |
| Hospital Management Database Analysis | SQL Server analysis of patients, doctors, appointments, treatments and billing across five linked tables, with patient age groups and billing summaries by month and branch | SQL |
B.Tech in Statistics, Ladoke Akintola University of Technology (LAUTECH), 2024
- LinkedIn: [https://www.linkedin.com/in/rofee-ah-tijani-713759253]
- Email: [feyishara161@gmail.com]
I'm open to AI/ML engineering, data science and analytics roles, as well as freelance work and collaborations.