Location: Chicago, New York, London, Hong Kong
Are you passionate about modeling and the pursuit of truth to achieve alpha? Are you a scientist at heart, who prefers to dive right in, research and test your ideas to identify trends where others don’t in vast quantities of data? Can you spot dead ends early and pivot quickly to peg prime opportunities?
Citadel is a worldwide leader in finance that uses next-generation technology and alpha-driven strategies to transform the global economy. We tackle some of the toughest problems in the industry by pushing ourselves to be the best again and again. It’s demanding work for the brightest minds, but we wouldn’t have it any other way. Here, great ideas can come from anyone. Everyone. You.
At Citadel, Quantitative Research (“QR”) is responsible for developing and testing automated quant trading strategies using sophisticated statistical techniques. We are seeking top students who are entrepreneurial self-starters and enjoy being in a fast-paced and dynamic environment for exciting opportunities in our automated quantitative trading businesses. This opportunity offers excellent exposure to a quantitative trading career path in one of the world’s leading global financial institutions.
If you aspire to:
- Mixing quantitative disciplines with creative problem solving to build tools that bring trading strategies to life
- Work in a team environment that closely integrates trading, quantitative research and technology
- Work on meaningful projects that directly impact global markets
- Invest in a career with purpose.
If you’ve got an interest in:
- Developing and optimizing trading signals (feature generation and model estimation)
- Building and refining monetization systems for trading signals
- Conducting research and statistical analyses in the evaluation of securities
- Working with large data sets to predict and test statistical market patterns
- Developing/continuously improving proprietary tools using the highest of software design standards
- Innovating new features from unconventional data sources
- Performing post-trade analysis
If you’ve proven you have:
- Advanced training in Computer Science, Mathematics, Statistics, Physics, Engineering or other highly quantitative fields
- An ability to communicate advanced concepts in a concise and logical way.
- Commitment to excellence and rigorous attention to detail
- Proficiency in statistical methods (e.g., machine learning, time-series analysis, pattern recognition, NLP)
- Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems
- Hands on programming experience in scripting (e.g. Python, Perl, Ruby, Smalltalk, etc) and compiled languages (C++ for Windows or Linux)