I am a systems-focused Software Engineer with a passion for high-performance computing and algorithmic optimisation. My expertise lies in low-level development (C/C++), where I build robust, memory-efficient systems from the ground up. I am currently leveraging my background in computational complexity to pivot into Financial Engineering, focusing on quantitative modelling and high-frequency data structures.
To bridge the gap between complex mathematical models and high-efficiency code. I thrive in environments where every microsecond and byte matters—whether it's optimising a sorting algorithm for market data or architecting a custom formatting engine.
A solo-developed implementation of the C standard library formatting engine.
- The "Solo Carry": Managed the complete development lifecycle independently, ensuring 100% Betty compliance and zero memory leaks.
- Tech: Variadic functions, custom buffer management, precision/width logic.
Comprehensive study of 15+ sorting methodologies and their computational trade-offs.
- Quant Focus: Analysis of stability and performance limits—essential for HFT and real-time data processing.
- Tech: Bitonic Sort, Quick Sort (Hoare/Lomuto), Merge Sort, Heap Sort.
Implementation of self-balancing trees (AVL) and Heaps.
- Fin-Tech Use: Foundations for order-book management and fast indexing in financial databases.
| Quarter | Focus Area | Goal |
|---|---|---|
| Q1 2026 | Object-Oriented C++ | Building modular trading engine components. |
| Q2 2026 | Statistical Modeling (R) | Implementing Monte Carlo and Black-Scholes simulations. |
| Q3 2026 | Data Structures for Finance | High-performance priority queues and lock-free concurrency. |
I am currently deepening my quantitative toolkit to transition into the Financial Engineering space:
- C++: Transitioning from procedural C to Object-Oriented C++ to build modular, high-performance trading engines.
- R: Learning statistical modelling, time-series analysis, and data visualisation for financial risk assessment.
- Quantitative Logic: Applying my algorithmic background to stochastic processes and derivative pricing models.
The most impactful financial models are only as good as the code they run on. My goal is to combine Quantitative Logic with System Efficiency to build:
- High-performance trading systems (HFT).
- Efficient risk-management simulations (Monte Carlo, Black-Scholes).
- Scalable data structures for real-time market feeds.