Quantitative developer and engineer with a PhD from the University of Oxford and an MSc from ETH Zürich, bringing over a decade of experience designing and deploying production-grade quantitative systems, spanning from high-frequency trading algorithms and low-latency GUIs/TUIs to large-scale ML pipelines and data infrastructure. Deep expertise across the full stack of quant development: research, implementation, testing, and deployment.
Senior Quantitative Developer
Digital Wave Finance AG · Zug
Mar 2025 – July 2026
Architected and implemented a low-latency data ingestion and aggregation backend for CeFi and DeFi market data using Python, enabling real-time data access for quantitative research and trading systems (FastAPI)
Designed and optimized scalable data schemas, APIs, and data pipelines to support high-throughput analytics workflows, improving data accessibility and reliability for downstream quant research and modeling
Designed and built a real-time terminal interface for monitoring and managing market-making activity on prediction markets, including live position tracking, order/quote management and risk alerts (Golang)
Led the implementation of secure, containerized development environments for agent-based systems, building a sandboxed Docker infrastructure and establishing security best practices for safe code execution and reproducibility
Built and productionized a funding rate forecasting system using ARIMA and XGBoost, incorporating time-series analysis, feature engineering, and model validation with Python (Scikit-learn, Darts)
Conducted statistical analysis of fund performance drivers, applying hypothesis testing, regression analysis, and quantitative modeling in Python to decompose and explain APR variability
Freelance Senior Quantitative Developer
Crypton Holdings · Cape Town
Oct 2024 – today
Developed and deployed automated trading systems based on technical analysis indicators for mid-frequency crypto markets, implementing robust, production-grade Python code, integrating algorithmic trading logic, technical indicators, and backtesting frameworks (Freqtrade)
Engineered a time-series forecasting pipeline for a price-directional LSTM forecasting model, focusing on data processing, model integration, and performance optimization with Python for real-time and batch inference (NumPy, Pandas, Darts, Scikit-learn)
Designed and maintained a scalable, containerized deployment infrastructure using Docker and Google Cloud Platform, enabling CI/CD workflows, automated model deployment, and high-availability trading systems
Senior Quantitative Developer
Mathrix AG · Zug
Oct 2022 – Jan 2025
Designed and developed a low-latency trading graphical user interface for crypto spot and derivatives (perpetuals, options) using Python, enabling real-time order execution, market visualization, and interaction for the trading desk (PySide/Qt)
Engineered a real-time monitoring and trade management system for hedging workflows, improving execution tracking, risk monitoring, and operational efficiency for traders using Python (PySide/Qt)
Maintained a high-frequency market-making system for live crypto markets, implementing alpha-generating strategies, low-latency execution logic, and real-time data processing using Python and Node.js
Led internal software engineering initiatives, including a Clean Code working group; delivered technical presentations on code quality, system design, and best practices to improve maintainability of the codebase
Conceptualized and developed a transaction cost–aware hedging framework, incorporating execution costs, and optimization techniques using JavaScript
Performed correlation and statistical analysis on crypto asset returns and US equity indices, applying time-series analysis, data analysis, and quantitative research methods in Python
Senior Data Scientist
SIX Group · Zurich
Jan 2019 – Oct 2022
Delivered a company-wide big data analytics platform on Microsoft Azure, enabling large-scale quantitative data processing and research workflows for Databricks using PySpark and Hadoop
Initiated and implemented a CI/CD pipeline on Azure DevOps, improving deployment reliability, code quality, and reproducibility for production-grade data
Developed a fraud detection system for the Swiss Stock Exchange, leveraging deep autoencoder neural networks on transaction-level market data using Python (Pandas, NumPy, PyTorch, TensorFlow)
Built a customer churn prediction model for financial services clients using deep learning techniques, handling real-world customer datasets with Python and PyTorch, supporting data-driven decision-making
Built NLP-based document scraping pipelines using AWS Textract and Rekognition, enabling automated extraction, processing and classification of structured and unstructured customer data
Full Stack Software Engineer
PwC Digital Experience Center · Zurich
May 2016 – Jul 2018
Led full-stack development of two high-performance e-commerce platforms, from architecture and implementation to maintenance, applying scalable database design, API development, and backend engineering using PHP7 and MySQL (Symfony2)
Developed a recommendation engine for a major Swiss e-commerce platform, integrating Google Cloud Vision API and building data-driven algorithms for content-based recommendations, highlighting feature extraction, model integration, and predictive analytics
Quantitative Developer
SwissQuant Group AG · Zurich
Apr 2011 – Jul 2014
Developed portfolio replication and optimization software for a Fortune 500 insurer, leveraging convex optimization solvers (Mosek, Gurobi, COIN-CLP) and MATLAB to deliver scalable, production-ready quantitative solutions
Built a fully automated stock-picking system in MATLAB using regression models, statistical filters, and quantitative strategies, integrating with MySQL for data management and backtesting workflows
Implemented stress-testing models integrated into a touch-enabled client advisory tool for a national private bank, applying risk modeling and scenario analysis with Java and MySQL
Delivered internal training seminars on convex optimization at SwissQuant, providing mentorship and knowledge transfer on quantitative finance modeling and algorithmic development