Quant Trader- Dublin

Posted Mar 24, 2026

Founded in 1999, Geneva Trading is a premier global principal trading firm with strategically located offices in Chicago, Dublin, and London. Our relentless focus on trading excellence combined with technological innovation has equipped us with a best-in-class proprietary trading platform, enabling us to compete at the highest levels in the global markets. Rooted in a culture of integrity, collaboration, and an unwavering passion for progress, we foster an environment of personal and professional excellence. Our nimble organizational structure and entrepreneurial spirit attract top-tier talent with a passion for innovation, laying the foundation and driving our consistent success in the industry. We are looking for Quant Traders to join our growing market-making team in Dublin. The ideal candidate has experience working at a proprietary trading firm and is looking for a position with more autonomy and the opportunity to assist with the rapid growth of a profitable trading desk. How You Can Make An Impact:

Managing positions and capitalize on trading opportunities
Monitor and troubleshoot our proprietary software and trading infrastructure
Analyze and model trading opportunities using real-world data. - Build and enhance tools that drive trading decisions and risk management. - Collaborate with traders and technologists to solve complex, high-impact problems. What We’re Looking For:
Strong programming skills in Python (or similar languages). - Solid understanding of statistics, probability, and optimization techniques. - Exposure to data analysis tools (e.g., R, MATLAB, Pandas, NumPy). - Curiosity about financial markets, algorithmic trading, and market microstructure. - Ability to think critically and communicate complex ideas clearly. - Ability to work in office. Preferred Extras
Experience with kdb+/q, SQL, or other database technologies. - Participation in trading competitions, math contests, competitive gaming, or poker. - Familiarity with machine learning techniques such as regression, neural networks, or SVMs.