Quantitative Researcher - Machine Learning
finance:systematicquant-researchIC4Quant
Compensation
Not disclosed
About Akuna:
Akuna Capital is an innovative trading firm with a strong focus on collaboration, cutting-edge technology, data driven solutions and automation. We specialise 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. At Akuna we have a flat structure, where the best idea wins.
Our Founding Partners, including 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, Singapore and London.
What you’ll do as a Quantitative Researcher at Akuna:
Akuna’s Quantitative Trading and Research team is looking to add experienced Quant Researcher specialized in Machine Learning to a team of mathematicians, statisticians and technologists. 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 Akuna’s strategy portfolio. In this role you will:
Develop trading strategies using statistical and machine learning algorithms
Design, conduct, and analyse experiments for a deep understanding of derivatives and financial markets
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
Requirements:
3+ years' strong professional work experience in statistics, machine learning, option tradin