New York

New York, midtown – Experienced Quantitative Portfolio Manager or Strategist

CloudQuant’s Global Systematic Trading unit is seeking experienced Quantitative Portfolio Managers and Strategists for the U.S. equity market.  Ideal candidates will have an MS or PhD in an Engineering or Pure Science discipline from a top school with formal academic coursework in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Digital Signal Processing, Portfolio Optimization, Linear Programming, Time Series Prediction, Factor Analysis, Fundamental Equity Valuation, Data Analytics and/or Genetic Algorithms.  Candidate should also have a proficiency in one of the following programming languages: Python (preferred) and/or C++, C#, Java or R.  Candidates should also be able to demonstrate a direct contribution to a systematic medium to high frequency, profitable, trading strategy or process in the U.S. equity market.  Experience with futures, FX and international equity trading is also a plus.

CloudQuant is an open and collaborative research environment and is seeking individuals with a strong entrepreneurial spirit, exceptional work ethic, and strong analytical skills to implement trading strategies.

CloudQuant is a diverse, energetic, work hard/play hard environment.  The firm provides cutting edge data science tools, investment capital, high performance elastic research infrastructure ideal for machine learning and other sophisticated modeling methodologies.  We provide tick data, fundamental datasets, sentiment data, alternative datasets as well as state-of-the-art trade execution tools through its proprietary collocated trading engines and trading software stack.

Opportunities are available in the Austin, Chicago, San Francisco, and New York with some options available for remote teams and team members.  For more information on CloudQuant, “The Trading Strategy Incubator”, visit our website at cloudquant.com.

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About CloudQuant

CloudQuant®  is “The Trading Strategy Incubator”.  It operates quantitative strategies developed internally, by its Global Systematic Trading Group, and, externally developed strategies created by crowd researcher who are paid a portion of the net trading profits as compensation.  The crowd researchers work with the CloudQuant Licensed Product Group.  CloudQuant Licensed Product Group has crowd researchers in over 130 counties on six continents.

CloudQuant is the Quantitative Trading and Asset Management subsidiary of Kershner Trading Group, LLC, a leading proprietary trading and technology firm with offices in Austin, Chicago and New York.

 

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