Quantitative Researcher - Machine Learning

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 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 Math 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.