Data Scientist | Systems Researcher | Builder
From statistical models to processor architecture.
I build systems that are theoretically grounded and practically deployable. My work spans two core domains: Applied Intelligence (data science, fraud analytics, quantitative systems) and Foundational Systems (processor design, OS, developer tooling).
Research Interests: Computer Architecture • RISC-V Extensions • Operating Systems • ML Systems • Financial Engineering • Quantitative AI
Sentinel | Real-time Nigerian transaction fraud detection with real-time scoring. Achieved 96.7% AUC-ROC with SHAP-based explainability.
Python FastAPI XGBoost SHAP Google Cloud
Live API Docs • Source Code
Matrix-RISCV | Custom RISC-V matrix multiplication extension for ML on constrained hardware. Achieved 50% fewer instructions optimized for edge environments. (arXiv manuscript in prep)
C RISC-V Assembly Computer Architecture
Source Code
Solvix | CLI for analyzing software systems before AI intervention. Evaluated on 31 real-world repos with an engineering-first approach.
Python CLI Static Analysis
Source Code
- WorldQuant University — Data Science Lab
- Preparing for MSc in Financial Engineering
- Advancing Matrix-RISCV research and developing Solvix into production
| Domain | Technologies |
|---|---|
| Languages | Python C C++ SQL |
| Data & ML | Pandas NumPy Scikit-learn XGBoost SHAP FastAPI |
| Systems | RISC-V Computer Architecture Operating Systems Linux |
| Tools | Git GitHub Google Cloud Jupyter |
Open to data science roles, research collaborations, engineering projects, and technical conversations.