Important : Please only apply if you are able to work on-site at our Zurich office every working day. This is a fully office-based role with no option for remote work.
About G-20
G-20 Group is a cross-asset trading firm headquartered in Switzerland, trading delta-one and derivatives markets globally. We combine startup agility with institutional-grade experience in proprietary trading, technology, and quantitative finance.
Role Overview
We are seeking an Algorithmic Quant Trader to develop and optimize systematic market-making strategies across digital assets and, where applicable, traditional markets. The role is focused on building high-performance algorithms that continuously price liquidity, manage inventory and risk, and capture spread and microstructure opportunities across fragmented electronic markets.
The successful candidate will have hands-on experience developing production market-making algorithms and a strong understanding of order books, execution, adverse selection, inventory management, and high-frequency market dynamics.
Key Responsibilities
• Design, develop, and optimize systematic market-making and liquidity-provision algorithms across spot, futures, perpetuals, and other derivatives.
• Develop dynamic quoting models incorporating spread optimization, inventory skew, volatility, liquidity, order-book dynamics, and adverse-selection risk.
• Research market microstructure and identify opportunities to improve fill quality, capture spreads, and reduce execution costs and information leakage.
• Build quantitative models for fair-value estimation, short-term price prediction, order placement, and inventory/risk management.
• Backtest and simulate strategies using high-frequency tick and order-book data.
• Analyze live strategy performance, including P&L attribution, fill rates, queue position, mark-outs, inventory, and execution quality.
• Work closely with traders and engineers to deploy research into low-latency production trading systems.
• Optimize strategies across multiple exchanges and liquidity venues, accounting for differences in fees, rebates, latency, market structure, and liquidity.
• Develop automated risk controls and monitoring for market-making strategies.
• Strong quantitative degree in mathematics, statistics, physics, computer science, engineering, or a related discipline. High-ranking universities preferred.
• Strong analytical and problem-solving skills.
• Strong written and verbal communication skills.
• Demonstrable professional experience developing algorithmic market-making strategies in crypto, equities, futures, FX, or other highly electronic markets.
• Deep understanding of market microstructure, limit-order books, execution algorithms, inventory management, and adverse selection.
• Strong programming skills, preferably Python plus C++ and/or Rust.
• Experience working with tick-level and order-book data and building quantitative research/backtesting frameworks.
• Understanding of statistical modelling, optimization, time-series analysis, and quantitative risk management.
• Experience taking strategies from research through backtesting and into live production.
• Strong commercial mindset with the ability to connect quantitative research directly to trading performance.
Preferred / Desirable Experience
• Direct experience in crypto market making or liquidity provision across major centralized and/or decentralized venues.
• Experience with high-frequency or low-latency trading systems.
• Knowledge of cross-venue pricing, arbitrage, hedging, and inventory optimization.
• Experience market making derivatives, particularly perpetual futures and options.
• Proven track record of improving market-making strategy profitability, scalability, or execution quality.
Right to work : This role is based in our Zurich office. Only candidates who reside in and who possess the pre-existing right to work in Switzerland without requiring company sponsorship need apply.
Join G-20 Group and be a part of a team that is at the forefront of financial markets, driving innovation and excellence in the sector.