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Quantitative Engineer · Lagos, Nigeria

(Quantitative finance & Software Engineering)

Ibrahim
Lanre

Quantitative Researcher at Celerfi, applying stochastic control, numerical methods, and quantitative modeling to derivatives, DeFi, and algorithmic trading systems. Competitive programmer with a strong foundation in algorithms and optimization. Founder & CEO of Mathelinux, a platform focused on quantitative education, research, and trading technology.

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About

I'm a Quantitative Researcher at Celerfi, where I focus on quantitative modeling, algorithmic trading strategies, optimization techniques, and DeFi market design. My work involves stochastic control, numerical methods, and mathematical finance, with applications to derivatives, liquidity provision, execution algorithms, and decentralized financial systems.

My academic work centres on high-performance numerical methods. My BSc thesis at the University of Lagos introduced an ADI/CN scheme for pricing multi-asset basket options combining alternating direction implicit methods for 2D Black-Scholes.

Alongside my research role, I run Mathelinux — a dual-track quantitative education platform I founded, targeting students breaking into quant finance and developers pivoting into quant engineering. I'm actively converting it into a full-time teaching and tooling business with a cohort-first launch model.

I hold LeetCode Knight tier (top 3%) and have a competitive programming background that I now channel into high-performance quantitative computing.

LeetCode

(Top 3%) globally
500+ Students taught across platforms
Experience

Where I've Worked

2026 – Present
Celerfi
Lagos, Nigeria

Quantitative Researcher

Quantitative research focused on algorithmic trading, market optimization, and decentralized financial systems. Working on mathematical models for crypto derivatives, execution strategies, liquidity provision, and on-chain market dynamics, while building quantitative infrastructure and numerical frameworks in Python and C++ for research, simulation, and production trading systems.

Machine Learning Stochastic Control & HJB PDEs & SPDEs DeFi/MEV/AMM C++ & Python MFG and Optimization
2023 – Present
Mathelinux
Lagos, Nigeria

Founder & CEO

Built and now lead Mathelinux, a dual-track quantitative education platform targeting students breaking into quant finance and developers pivoting into quant engineering. Designed the full curriculum (10-module syllabus covering stochastic calculus, numerical methods, C++ systems, and algo-trading) and system architecture. Actively building toward a cohort-first launch model with AI-powered Socratic tutoring and code-review agents.

Quantitative Research & Education TypeScript / Node.js React AWS Redis / PostgreSQL
Projects

Selected Work

001
2D Black-Scholes Numerical PDE Solver (ADI/CN)

Designed and implemented ADI–Crank–Nicolson numerical solvers for the 2D Black–Scholes equation in multi-asset option pricing. The project involved finite difference methods, numerical stability and convergence analysis, and rigorous error evaluation, providing an efficient framework for solving high-dimensional derivatives pricing problems. Developed as part of my BSc thesis in computational mathematics and financial engineering.

Python Computational Complexity ADI Schemes Black-Scholes
002
O(1) Order Book Simulator

High-performance order book replicating exchange mechanics — limit/market orders, price-time priority, and full order lifecycle. Engineered for minimal latency and high throughput via cache-friendly data structures and allocation-minimizing design patterns in modern C++.

C++17 HPC Low-Latency Market Microstructure
003
MEV Extraction Engine (HJB/QVI)

Stochastic control–based MEV bot architecture grounded in HJB equations and quasi-variational inequalities. Seven-phase system with Rust/ethers-rs on-chain execution and Python/C++ offline PDE solving. Frames MEV extraction as an optimal stopping and impulse control problem.

C++/Python HJB QVI DeFi Optimal Control
Skills

Technical Stack

Quant / Math

Stochastic Measure & SPDE Volterra & Rough Volatility Numerical PDE Solvers Kalman & Particle Filters Market Microstructure & Hawkes ADI Schemes & TDA PINNs

Languages

C++ 11/17/20 Python Jupyter Notebook TypeScript / JavaScript Golang MATLAB

Frameworks & Tools

React Node.js NestJS Django Docker Kubernetes AWS Redis PostgreSQL Prometheus / Grafana

Domains

Quantitative Research & Derivatives Pricing DeFi & CeFi HFT / Low Latency Software Engineering & System Design Market Microstructure & HPC Competitive Programming
Education

Academic Background

MSc in Financial Engineering
WorldQuant University
Sep 2025 – Sep 2027
BSc in Computational & Applied Mathematics
University of Lagos, Nigeria
Thesis: A Class of ADI Schemes for the Numerical Solution of the 2D Black-Scholes Equation for Multi-Asset Basket Option Pricing
Sep 2021 – Aug 2025
Writing

Recent Articles

From Dense to Sparse Part 2
From Dense to Sparse: Numerical Methods for Quant Finance (Part 2)
Read on Medium ↗
From Dense to Sparse Part 1
From Dense to Sparse: Numerical Methods for Quant Finance (Part 1)
Read on Medium ↗
Lévy Model in Finance
From Diffusion to Jumps: Lévy Model in Finance
Read on Medium ↗
Girsanov and Radon-Nikodym
Changing the Odds, Pricing the Future: Girsanov and Radon‑Nikodym
Read on Medium ↗
SPDEs
Stochastic Partial Differential Equations: Why Classical PDEs Fail in Markets
Read on Medium ↗
Hawkes Process Order Book
High-Frequency Order Book Dynamics: A Multivariate Hawkes Process Approach
Read on Medium ↗
View all articles on Medium ↗
Contact

Let's Talk
Quant.

Open to research collaborations, quantitative roles, low-level engineering and conversations about quant finance, derivatives pricing, DeFi strategy, or the Mathelinux platform.

ibrahimlanre1890@gmail.com linkedin.com/in/ibrahim-lanre github.com/LANREADE +234 901 925 8627