Quant Trading Engineer

CW ASSET MANAGEMENT PTE. LTD.; Singapore; On-site; SGD 120,000 - 240,000; Full time

Job summary

CW ASSET MANAGEMENT PTE. LTD. is seeking a seasoned quantitative trading professional to design, validate, and optimize digital asset trading strategies.

The role involves market-making activities, risk management, and developing robust trading systems and data pipelines. The ideal candidate will have 3+ years of experience in quantitative trading or research, with strong math and statistical skills, and proficiency in Python, Golang, and C++.

Qualifications

• 3+ years of experience in quantitative trading or quantitative research, with practical experience in digital asset markets.
• Strong foundation in mathematics, statistics, and probability.
• Experience with market-making strategies or liquidity management and understanding of key concepts like quoting and risk exposure.

Responsibilities

• Strategy research and trading execution: design, validate, and optimize trading strategies for digital assets.
• Financial product and trading mechanism design: develop trading rules and market mechanisms to improve user experience.
• Market making strategy support: liquidity strategy design, order book management, and inventory risk control.
• Data analysis and strategy iteration: feature extraction, backtesting, and performance optimization using market data.
• Trading system development: build strategy execution systems and data pipelines, translating them into executable logic.
• Live trading monitoring and risk management: track performance and mitigate risk across strategies.
• Engineering implementation: leverage Python, Golang, or C++ to implement strategy modules and API integrations.

Skills

Quantitative trading

Python

Golang

C++

Data analysis

Strategy backtesting

Tools

Python

Golang

C++

Job description

Responsibility

1. Strategy Research and Trading Execution: Participate in the design, validation, and optimization of quantitative trading strategies, including but not limited to short-term trading, arbitrage, market making, trend strategies, and risk hedging.
2. Financial Product and Trading Mechanism Design: Participate in the design of trading products, trading rules, riskparameters, and market mechanisms, optimizing trading experience based on user needs and market structure.
3. Market Making Strategy Support: Participate in liquidity strategy design, order book management, inventory management, risk exposure control, and other market-making related activities.
4. Data Analysis and Strategy Iteration: Conduct feature analysis, signal extraction and research, strategy backtesting, and continuous optimization based on market data.
5. Trading System Development: Participate in the design and development of strategy execution systems, data processing pipelines, and related trading tools, and transform them into executable trading logic.
6. Live Trading Monitoring and Risk Management: Track strategy performance, analyze trading results, optimize execution efficiency, and control strategy risks.
7. Engineering Implementation: Possess basic engineering capabilities and independently complete strategy module development, data processing, and API integrations.

Requirement

1. 3+ years of experience in quantitative trading or quantitative research, with practical experience in digital asset markets. Candidates from funds, market-making teams, or exchanges are preferred.
2. Experience in funds, quantitative teams, exchanges, market makers, or related fields is preferred.
3. Deep understanding of digital asset markets, including spot trading, derivatives, order books, and liquidity mechanisms, with practical trading experience.
4. Experience in financial product design or trading mechanism design, with the ability to understand and break down core rules within trading products.
5. Experience with market-making strategies or liquidity management, with an understanding of key concepts such as quoting, inventory, and risk exposure.
6. Strong foundation in mathematics, statistics, and probability, with the ability to conduct strategy analysis and model validation.
7. Strong engineering capabilities, with the ability to use languages such as Python / Golang / C++ for strategy implementation, data processing, or trading tool development.
8. Ability to independently complete data analysis, strategy backtesting, performance evaluation, and strategy iteration.