Quantitative Researcher - Machine Learning
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 conceptualised Akuna in their hometown of Sydney.
They opened the firm's first office in **** 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 an experienced Quant Researcher specialised 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 optimisation algorithms for portfolio construction
Develop quantitative models describing market behaviour
Advance existing initiatives and explore opportunities for new research topics
Requirements
3+ years' strong professional work experience in statistics, machine learning, option trading or related area
Hands-on experience using a modern ML tool in a trading application
Bachelors, Masters or PhD in a technical field – Statistics, Computer Science, Mathematics, Physics, Engineering (or a related subject), must be completed upon employment
Proven research background in academic or professional environment
Experience building mathematical models for complex real-world problems
Expertise in maths and statistics
Strong Python programming skills
Machine Learning/Data Science experience with modern and classic ML tools such as Neural Networks, Tree models, and Ensemble Learning, applied to large and complex data sets in a trading application
Qualities that make great candidates
Collaboration, teamwork, and excellent communication skills
Strong drive to deliver meaningful results
Financial experience or knowledge of options trading is a plus
Please note:If you apply to multiple roles, you may be asked to complete multiple coding challenges and interviews.
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