A small, collaborative, and entrepreneurial team is seeking a Quantitative Developer to liaise /advise investment teams on their systems development needs and translate them into working investment solutions. This can sometimes include signal generation using statistics as well as novel techniques including machine learning applications. This team is also involved in building solutions for core functions with a view of subsequently scaling to large sized strategic tools. This role is ideal for somebody with a strong background in quantitative finance, computer science, mathematics or a related field, who is passionate about solving complex problems and providing generalized, reusable solutions.

Principal Responsibilities

• Implement quantitative and technical tools for shortening the time-to-market for incoming systematic portfolio managers This translates to full stack development from signal to trade.
• Primary focus will be on: data gathering/caching, research/production platform development including interaction with in-house trading systems
• Combine sound financial insights and statistical learning techniques to explore, analyze, and harness a large variety of datasets
• Develop and maintain tools and software to support research and trading activities across different trading pods
• Implement business logic for some of core functions such as execution monitoring, inventory / scarce resource management, risk controls in an agile manner and help translate/transition into strategic tools.
  
  

Preferred Technical Skills

• Master’s or PhD degree in Computer Science, Financial Engineering, Mathematics, or Physics.
• Strong Python skills including Pandas, NumPy, sklearn, experience with larger scale development projects
• Strong mathematical background, including a solid understanding of ML methods and technologies
• Experience with large datasets and knowledge of Relational/Columnar Databases (KDB a plus) and REST APIs
  
  

Preferred Experience

• Minimum of 3 years experience as a quantitative developer, quantitative researcher
• Deep knowledge of financial markets, instruments and typical trading strategies
• Experience with live and historical market data at varying frequencies
• Excellent communication, analytical, and problem-solving skills
  
  

Highly Valued Relevant Experience

• Experience with machine learning, statistical analysis, data visualization techniques
• Cross-asset class knowledge, including solid equities experience
• Some Cloud (AWS/Google cloud) experience a plus, Docker, Airflow also a plus
• Knowledge of Asian market nuances a big plus.

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