Quantitative Development Intern - Quant Trading & Research, Summer 2018
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 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 Cambridge (USA).
What you’ll do as a Quantitative Development Intern on the Quant Trading & Research team at Akuna:
Akuna’s Quantitative Trading and Research team creates trading strategies scientifically by combining its quantitative expertise with sophisticated understanding of derivatives and financial markets. The team is looking to add Quantitative Development Interns who will make a direct and measurable impact on our trading decisions and performance.
The successful candidate will have a strong programming background, familiarity with mathematical techniques and the fluency to leverage both skills to produce trading solutions and high-performance production code. In this role you will:
- Design and develop production code of trading strategies: pricing models, execution logic and performance optimization along with researchers, traders and system engineers
- Analyze and incorporate market signals in our trading systems
- Advance existing codebase and propose new solutions and improvements
Qualities that make great candidates:
- Pursuing a BS/MS/PhD in a technical field – Engineering, Computer Science, Math, or Physics
- Strong Python or C++ programming background
- Experience in object-oriented programming
- Exposure to linear algebra and introductory statistics
- Desire and ability to learn the intricacies of financial markets
- Experience with generic and/or parallel programming
- Deeper understanding of any of the following fields: Linear Algebra, Numerical Methods, Statistics, Optimization, Signal Processing, Computer Architecture, Machine Learning
- Exposure to financial markets and trading
- Graduation date of August 2020 or prior
Location: Chicago, IL