John Alexandre Borkowski
Computer Science & Mathematics at UT Austin. I build quantitative models and the software that runs them, most recently on the Quantitative Trading desk at Goldman Sachs.
Experience
Goldman Sachs
Credit curve modeling and risk factor work for the FICC credit desk.
AllianceBernstein
Alpha signal research and regime models for the Quantitative Portfolio Modeling team, plus a secure mobile app view for serving encrypted client financial documents.
Austin Venture Strategy
Built prototypes and MVPs for UT tech startups.
UT Wakeboarding Team
Ran a 150-member club and built its registration and scheduling app.
Projects
Quantum Chess Engine
A chess engine where pieces can enter superposition and become entangled, built on a hand-written complex-vector state space and a custom linear algebra library for unitary transformations and measurement collapse.
FinDB
A stock trading web app with real-time market data, portfolio management, trade execution, and a volatility screener pricing market-implied vols via Bjerksund-Stensland.
Pipelined CPU, Cache Simulator & Pintos OS
A pipelined CPU and cache simulator with hazard detection and replacement policies, plus multithreading and virtual memory subsystems for a Pintos-based OS.
Skills
- Languages
- Python, C++, C, Java, SQL, R, JavaScript, TypeScript
- Libraries
- Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, PyTorch, TensorFlow, React, Flask, Django
- Infrastructure
- Linux, Bash, AWS (S3, boto3), GCP, Docker, Git, MongoDB
- Spoken
- English, French, Spanish (fluent)
Education
The University of Texas at Austin
Coursework: Algorithms & Complexity, Data Structures, Computer Architecture, Operating Systems, Probability, Statistics, Machine Learning, Artificial Intelligence, Linear Algebra, Finance, Quantum Informatics