Quantitative Research Internship- Machine Learning, Summer 2018
Akuna Capital - Chicago IL

Internship Category: Paid

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  • 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 firms 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 Cambridge (USA).

    What youll do as a Quantitative Research Intern at Akuna:

    Akunas Quantitative Trading and Research team is looking to add Quantitative Research Interns to a team of mathematicians, statisticians and technologists for our 10 week internship Akunacademy in our Chicago office. This team creates trading strategies scientifically by combining its quantitative expertise with sophisticated understanding of derivatives and financial markets.

    We are looking for talented researchers who can apply and develop machine learning algorithms to contribute to Akunas 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:

    • Pursuing a Masters or PhD in Statistics, Computer Science, Mathematics (or a related subject)
    • Expertise in statistics and machine learning
    • Intermediate programming skills in Python (C++ is a plus)
    • Experience of working on practical applications with real-world datasets
    • Financial experience is not a requirement
    • Graduation date of August 2020 or prior
    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 firms 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 Cambridge (USA).

    What youll do as a Quantitative Research Intern at Akuna:

    Akunas Quantitative Trading and Research team is looking to add Quantitative Research Interns to a team of mathematicians, statisticians and technologists for our 10 week internship Akunacademy in our Chicago office. This team creates trading strategies scientifically by combining its quantitative expertise with sophisticated understanding of derivatives and financial markets.

    We are looking for talented researchers who can apply and develop machine learning algorithms to contribute to Akunas 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:

    • Pursuing a Masters or PhD in Statistics, Computer Science, Mathematics (or a related subject)
    • Expertise in statistics and machine learning
    • Intermediate programming skills in Python (C++ is a plus)
    • Experience of working on practical applications with real-world datasets
    • Financial experience is not a requirement
    • Graduation date of August 2020 or prior
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