Quantitative Development Intern- Data Analysis, Summer 2018
We are looking for Quantitative Development Interns to join Akunacademy in our Chicago office to work with a world class team of Quantitative Developers and Traders. Our interns come from many different backgrounds but all share a passion for solving the complex and challenging problems only found in the financial markets.
At Akuna Capital, we match our talented interns’ skills and interests with our team goals. At the end of your Quantitative Development Internship at Akuna Capital you should expect to have gained experience and exposure to the financial markets, completed complex, non-trivial projects that directly impact our business goals, and participated in all aspects of the quantitative research process at Akuna Capital.
If you have ever had an interest in working in the exciting, complex and competitive area of the financial markets, there is no better place to work than Akuna Capital.
In the past, Quantitative Development Interns at Akuna have:
- Identified and defined significant algorithm improvements to our trading strategies
- Conducted self-driven data analysis projects on complex trading topics
- Applied Machine Learning to our expansive financial datasets
- Implemented frameworks for validation and testing of complex trades
- Created beautiful visualizations to communicate complex analysis results to team members
- Developed core data infrastructure used daily by our team
- Developed tools for monitoring our trading system performance
Qualities that make great candidates:
- Currently pursuing a Bachelors, Masters or Ph.D. in a technical field - Physics, Math, Engineering, Computer Science, or equivalent
- Passionate, pragmatic problem solver with the ability to independently pursue solutions to complex problems
- Demonstrated experience developing software using Python on Linux. Experience with the common Python data libraries (Pandas, numpy, etc…) is a strong plus
- Ability to communicate complex technical topics in a clear and concise way
- Demonstrated experience with data analysis, either on a personal, school, or research project, is a strong plus