Senior Derivative Quantitative Trader

Operate and help develop the group’s cross country, cross asset, large-scale, low-latency trading systems; Apply sophisticated machine learning techniques to a wide variety of datasets; Examine and test relevant research papers to determine their relevancy and impact; Use rigorous technical models to develop sophisticated data models to shape insights into how markets operate and behave; Develop creative solutions to challenging real-world trading issues by building out new quantitative models and strategies through application of stochastic and optimization methods; Devise or apply independent models or tools to help verify results of analytical systems; Provide application or analytical support to traders on issues such as valuations or data; Use strong communication skills (verbal and written) to confer with other financial engineers or analysts on trading strategies, market dynamics, or trading system performance to inform development of quantitative techniques; Identify, track, or maintain metrics for trading system operations; Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope; Research and develop quantitative and arbitrage strategies across asset includes including equities, foreign exchange, and futures; Program in multiple computer languages; Manage multiple competing priorities in a fast-paced and challenging environment. Salary: $150,000 - $230,000 per year.

MINIMUM REQUIREMENTS: Bachelor’s degree or U.S. equivalent in Applied Mathematics, Operations Research, Statistics, Computer Science, Computer Engineering, Physics, or related field plus 3 years of professional experience performing quantitative and automated trading in a team-based environment utilizing large-scale, low-latency C++ trading systems and data platforms.

Must also have the following special skills: 3 years of professional experience programming in Python, R, or Matlab; 3 years of professional experience utilizing machine learning libraries and techniques including Python Libraries, Dask, and Keras; 3 years of professional experience verifying results of analytical systems using independent models or tools including Bloomberg; 2 years of professional experience working within a High Frequency Trading environment; and 2 years of professional experience utilizing distributed data research platforms and Data Clusters for machine learning.

CONTACT: Please email resume to: hr@hap-capital.com Must specify Ad Code YZAL.

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