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Quantitative Trader in Hong Kong

7 active opportunities · Updated for October 2026

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Explore current quantitative trader jobs in Hong Kong. Use filters to narrow by work mode, employment type, experience and date posted.

C
Crypto.com
📍 Hong Kong• Full-time• Hybrid
15 days ago

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets, including spot and derivatives. We are looking for an experienced Systematic Trader to develop, operate, and continuously improve systematic strategies in fast-moving electronic markets. Responsibilities: Operate and manage systematic trading strategies and frameworks across prediction markets, equities, and crypto, including spot, perpetuals, futures, options, and other derivatives. Monitor live trading, P&L, positions, risk, and execution performance. Research, backtest, deploy, and improve systematic trading strategies. Identify new trading opportunities across markets, products, exchanges, and venues. Analyze strategy and execution performance, including fills, slippage, adverse selection, transaction costs, and latency. Optimize strategy parameters, position sizing, execution, and risk controls. Work closely with quantitative developers and researchers to implement new strategies and improve trading systems. Participate in local trading coverage and rotating weekend coverage. Requirements: 4+ years of experience in systematic, quantitative, electronic, proprietary, or market-making trading. Demonstrated experience developing, operating, or improving profitable trading strategies. Strong understanding of market microstru

pythonsqlc++
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C
Crypto.com
📍 Hong Kong• Full-time• Hybrid
15 days ago

The Trading team develops and operates quantitative trading strategies across prediction markets, equity markets, and crypto markets . We are looking for a Trading Operations & Support Analyst to support live systematic trading, ensure smooth day-to-day operations, and help improve the reliability and efficiency of our trading systems and processes. Responsibilities: Monitor live trading systems, strategies, orders, positions, P&L, and risk. Act as the first line of support for trading, execution, exchange connectivity, and production issues. Investigate and resolve order, position, P&L, reconciliation, and trading-system exceptions. Coordinate with traders, quantitative developers, exchanges, brokers, and other counterparties to resolve live trading issues. Support strategy deployments, system releases, testing, and production changes. Monitor exchange and market events, outages, connectivity issues, and other operational risks. Analyze trading and operational metrics to identify issues and improve processes. Develop tools and automation to improve monitoring, reconciliation, reporting, and trading operations. Maintain operational procedures and controls for production trading. Participate in local trading coverage and rotating weekend coverage. Requirements: 3+ yea

pythonsqlfinance
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P
13 days ago

Job Responsibilities A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. You will gain exposure to a variety of activities, which may include: Developing automated equities trading applications and real-time analytics Optimizing data ETL pipelines, persistent / in-memory caches and SQL databases Work alongside quant researchers developing quant signals. Improving signal research and trading tools infrastructure Desirable Candidates Undergraduate or higher degree in computer science, machine learning, or other quantitative discipline 5+ years of experience at a hedge fund, major investment bank, or quantitative trading firm Strong programming experience in Python with production-level coding quality Experience with containerization and orchestration technologies, particularly Docker Experience with Unix environment and shell scripting Knowledge of profiling (e.g. VisualVM, async-profiler) and code optimization is a plus Knowledge of statistics and machine learning is a plus Willing to take ownership of his/her work, working both independently and within a small team Prior experience in the financial services industry is a plus Commitment to the highest ethical standards

pythonsqldocker
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P
13 days ago

JOB RESPONSIBILITIES A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. You will gain exposure to a variety of activities, which may include: Developing automated equities trading applications and real-time analytics Optimizing data ETL pipelines, persistent / in-memory caches and SQL databases Work alongside quant researchers developing quant signals. Improving signal research and trading tools infrastructure DESIRABLE CANDIDATES Undergraduate or higher degree in computer science, machine learning, or other quantitative discipline 5+ years of experience at a hedge fund, major investment bank, or quantitative trading firm Strong programming experience in Python with production-level coding quality Experience with containerization and orchestration technologies, particularly Docker Experience with Unix environment and shell scripting Knowledge of profiling (e.g. VisualVM, async-profiler) and code optimization is a plus Knowledge of statistics and machine learning is a plus Willing to take ownership of his/her work, working both independently and within a small team Prior experience in the financial services industry is a plus Commitment to the highest ethical standards

pythonsqldocker
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ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. ROLE The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance. RESPONSIBILITIES Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas. Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization. Maintaining and improving portfolio trading in production environments. REQUIREMENTS Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline. 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus. Str

pythonmachine learning
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The Quant Trading team is responsible for trading and managing risks associated with different crypto products, including spots and derivatives. The team develops and implements trading strategies in fast-paced and complex trading environments. Job Responsibilities Data Platform & Analytics Design, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies Design and build unified analytics engine designed for processing large-scale data using Apache Spark and related tools Develop and optimize analytical data models for time-series, financial metrics, and trading activity Implement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture Build idempotent data pipelines with robust backfill and reconciliation capabilities Create comprehensive monitoring for data quality, freshness, and pipeline reliability AI Platform Development Design, build, and operate internal AI platforms serving multiple trading teams Build reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows Create and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability Job Requirements Mandatory Foundations</str

pythonjavasql
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About Cubist: Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role: Cubist is looking for a support engineer/quantitative developer who will work on a growing L2/L3 support team for quantitative trading systems, high‑frequency trading infrastructure, real time analytics, and research infrastructure. This role will require close collaboration with multiple teams at Cubist, including multiple Portfolio Manager (PM) teams, Central Research Technology, and Execution Services. The role offers career growth through the opportunity to work on the development of the underlying systems. Role/Responsibilities: Troubleshooting/resolution of quantitative trading systems and other live analytics processes System monitoring, including development of better processes and tools New feature development in Python/C++ Configuration and change management Onboarding assistance Requirements: 2+ years of professional support and/or software engineering experience Experience with trading systems support (co-located low-latency systems a strong plus) Fluency with C++, Python and SQL Familiarity with software delivery lifecycle and production deployment Cloud experience is a strong plus T

pythonsqlc++
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