Algorithmic Trader (Hong Kong) at G-20 Group

Hong Kong, Hong Kong Island, Hong Kong S.A.R. -

Full Time

Start Date

Immediate

Expiry Date

28 Jan, 26

Salary

0.0

Posted On

30 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Algorithmic Trading, Market Making, Quantitative Research, Software Engineering, Risk Management, Data Analysis, Performance Optimization, Collaboration, Communication, Execution Strategies, Liquidity Dynamics, Trading Systems, Python, C++, Statistical Trading, High-Frequency Trading

Industry

Investment Management

Description

About G-20 The G-20 Group is a pioneer in Quantitative Trading systems in cross-asset markets. Headquartered in Switzerland, we operate at the intersection of Quantitative Research, Software Engineering and Trading. The team combines a startup mindset with extensive experience in proprietary Trading, Technology and Quantitative Finance. Role Overview We are seeking an experienced Algorithmic Trader with a background in Market Making strategies to join our trading team. The ideal candidate will have experience in designing, implementing, and managing automated market making strategies across multiple asset classes (FX, crypto, commodities, or equities). You will be responsible for optimizing quoting and inventory management algorithms, monitoring real-time performance, and identifying new opportunities in both liquid and fragmented markets. This role combines quantitative research, technology, and trading expertise, offering high autonomy and direct PnL ownership within a dynamic, data-driven environment. Key Responsibilities Manage algorithmic trading strategies in real-time. Continuously refine quoting, hedging, and execution algorithms to improve profitability and reduce slippage. Monitor algorithm performance, market conditions, and risk exposures during trading sessions. Collaborate with quants, developers, and data scientists to enhance models, signals, and execution logic. Analyze historical trading data to identify performance trends and optimize parameters. Ensure compliance with market regulations, exchange rules, and internal risk controls. Contribute to strategy development and market microstructure research. Troubleshoot algorithmic issues, ensuring system uptime and reliability. Degree in Finance, Mathematics, Physics, Computer Science, Engineering, or a related field from a top-tier university. At least 5 years of experience in algorithmic or electronic trading, preferably in spot markets (FX, crypto, equities, or commodities). Proven track record of generating consistent profits (PnL >$2m for more than 3 years). Strong understanding of market microstructure, liquidity dynamics, and execution strategies. Familiarity with real-time trading systems, data feeds, and market connectivity. Proven ability to monitor and manage risk in fast-moving, high-volume markets. Strong analytical and quantitative skills, with attention to performance metrics and optimization. Excellent communication and teamwork skills, with the ability to collaborate effectively across teams. Preferred / Desirable Experience Proficiency in Python, C++, or another trading-related programming language. Experience in market making, arbitrage, or statistical trading strategies. Exposure to low-latency or high-frequency trading environments. Familiarity with cloud infrastructure, containerized systems, or distributed data processing. Right to work: We are hiring for our London, Zurich, Hong Kong and Singapore offices. Only candidates who possess the pre-existing right to work in London, Zurich, Hong Kong or Singapore without requiring company sponsorship need apply. Join G-20 and be a part of a team that is at the forefront of financial markets, driving innovation and excellence in the sector. Deadline for applications: November 6th, 2025

Responsibilities

Manage algorithmic trading strategies in real-time and continuously refine quoting, hedging, and execution algorithms to improve profitability. Monitor algorithm performance, market conditions, and risk exposures during trading sessions while collaborating with quants, developers, and data scientists.