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Role Description

HAP Capital is seeking an experienced quantitative researcher with advanced data analytic and statistical modeling expertise to join the Quantitative Strategies Group. QSG seeks to identify pricing and volume dynamics in electronic markets. Insights gleaned about liquidity and market micro-behavior are used to model the price discovery process. The role will be responsible for driving signal research and development. The ideal candidate will demonstrate an ability to conceptualize trading phenomenon, formulate research objectives, and develop tradeable alphas: 

hypothesis –> data collection –> research & modeling –> definition –> evaluation –> c++ implementation

The candidate will demonstrate deep comprehension of statistical inference techniques, feature specification, model fitting and evaluation, sim-live fidelity, machine learning, numerical methods, market microstructure, and large-scale high-density data manipulation. As a Quantitative Researcher you will:

  • Research Alpha Ideas with a view to enhancing predictive capability of new and existing models
  • Identify Concrete Research Objectives for advancing profitability of live trading strategies
  • Implement High-Speed Computational Code in a variety of programming languages
  • Develop and test data-centric theories aimed at understanding intraday liquidity dynamics
  • Build research tools and applications for processing and examining market and trading data
  • Drive Technical and Intellectual Innovation on all R&D initiatives the team undertakes


  • Graduate degree in Applied Math, Statistics/ML, Physics, Computer Science, or similar
  • Proficiency in advanced data research & modeling using Python and/or R
  • Comfort in C++ with experience interacting with large-scale production applications
  • Extensive knowledge and expertise designing statistical inference models and predictive analytics
  • Extensive knowledge and experience with high-volume high-dimensional data modeling

Additional skills/experience that will reflect favorably

  • PhD in Applied Math, Statistics, ML, Computer Science/Engineering, Physics or similar
  • Deep insights into global financial exchange micro-structure and micro-behavior
  • Prior experience managing Equities and/or Futures Statistical Arbitrage or HFT strategies
  • Experience originating alpha/strategy development in an unprecedented environment or scale