Software & ML Engineer | Quantitative Trader
Operating at the intersection of Blockchain Data, AI, and Quantitative Systems
I’m a Software and Machine Learning Engineer with a strong foundation in quantitative research and blockchain data systems. My work centers around designing and implementing autonomous trading models, data-driven infrastructure, and AI-powered analytics for decentralized markets.
I’m particularly passionate about integrating financial theory, machine learning, and on-chain transparency to redefine how markets are understood and automated.
- 🔭 Currently building: Quantitative crypto trading bots and blockchain data pipelines
- 🧠 Focused on: Market microstructure modeling, predictive analytics, and smart contracts
- 🌱 Learning: Rust for high-performance systems and reinforcement learning for adaptive trading
- 💬 Ask me about: Algorithmic trading, on-chain data analysis, or AI model optimization
- ⚙️ Philosophy:"Code is an experiment; data is the truth."
Languages: Python • Java • Rust • SQL
Domains: Quantitative Finance • Blockchain Analytics • Machine Learning
Tools & Frameworks: Pandas • NumPy • PyTorch • FastAPI • PostgreSQL • Docker • AWS
- Quantitative Research: Statistical modeling, backtesting, and alpha generation
- Blockchain Data Engineering: Extract-transform-load (ETL) systems for on-chain data
- Machine Learning Applications: Time-series forecasting, market regime detection
- Software Engineering: High-performance systems and API design for data automation
B.Sc — Banking and Finance
Certifications:
- FMVA® — Corporate Finance Institute
- FRM® (In View) — Global Association of Risk Professionals
Focus: Data Science, Quantitative Methods, Financial Modeling
- Email:oluwatunmise1olaoluwa@gmail.com
- LinkedIn:linkedin.com/in/tunmiseolaoluwa
- X (Twitter):@apostleoffin
“Markets are conversations in math — I build the translators.”