Quantitative Researcher- Machine Learning
Akuna CapitalShanghaiUpdate time: August 2,2019
Job Description
上海市
About Akuna:
Akuna Capital is a young and booming trading firm with a strong focus on cutting-edge technology, data driven decisions and automation. Our core competency is providing liquidity as an options market-maker – meaning we provide competitive quotes that we are willing to both buy and sell. To do this successfully we design and implement our own low latency technologies, trading strategies and mathematical models.

Our Founding Partners, Andrew Killion and Mitchell Skinner, first conceptualized Akuna in their hometown of Sydney. They opened the firm's first office in 2011 in the heart of the derivatives industry and the options capital of the world – Chicago. Today, Akuna is proud to operate from additional offices in Sydney, Shanghai and Boston.

What you'll do as a Quantitative Researcher at Akuna:
Akuna's Quantitative Trading and Research team is looking to add Quant Researchers to a team of mathematicians, statisticians and technologists. This team creates trading strategies scientifically by combining its quantitative expertise with a sophisticated understanding of derivatives and financial markets.

We are looking for talented researchers who can apply and develop machine learning algorithms to contribute to Akuna's strategy portfolio.In this role, you will:

  • Develop trading strategies using statistical and machine learning algorithms
  • Design and implement optimization algorithms for portfolio construction
  • Advance existing initiatives and explore opportunities for new research topics
Qualities that make great candidates:
  • 2+ years of strong professional work experience in statistics,quantitative research,quantitative development
  • Bachelor,Masters or PhD in Statistics,Computer Science,Mathematics
  • Programming skills in Python is a must (C++ is a plus)
  • Experience working on practical applications with real-world data sets
  • Good English and Chinese communication skill
  • Good understanding of machine learning

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