Akuna Capital is an innovative trading firm with a strong focus on collaboration, cutting-edge technology, data driven solutions and automation. We specialize in providing liquidity as an options market maker – meaning we are committed to providing 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, including Akuna's CEO Andrew Killion, 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.
Akuna Sydney opened in early 2018 and is at the center of Akuna’s Asian trading operations. Akuna’s focus in Asia is currently trading HK, Korea, cryptocurrencies and US night markets and is looking to expand to trading on all major Asian exchanges. Employees will work together towards achieving Akuna’s goals across all areas of the business, including trading and desk buildout, cutting-edge research and data analysis, strategy creation, and building ultra-low-latency trading systems that are tailored to local market conditions.
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
- Help identify, design, backtest and optimize low latency strategies using big data
- Build metrics to evaluate strategy execution and perform post trade analysis
- Design and implement optimization algorithms for portfolio construction
- Develop quantitative models describing market behavior
- Advance existing initiatives and explore opportunities for new research topics
Qualities that make great candidates:
- 2+ years of strong professional work experience in statistics, machine learning or related area
- BS/MS/PhD degree in a technical field – Engineering, Computer Science, Math, Physics, or similar
- Proven research background in academic or professional environment
- Basic programming skills in Python (C++ is a plus)
- Expertise in statistics
- Experience building mathematical models for complex real-world problems
- Financial experience is not a requirement
- Experience in machine learning is a plus