Job Description
At Citadel Securities, a leading global market maker, our team of quantitative researchers models the markets and brings trading strategies to life every day. Specifically, this team develops and tests automated quant trading strategies using sophisticated statistical techniques. You'll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world.
Your Objectives
- Conceptualize valuation strategies, develop, and continuously improve upon mathematical models and help translate algorithms into code
- Back test and implement trading models and signals in a live trading environment
- Use unconventional data sources to drive innovation
- Conduct research and statistical analysis to build and refine monetization systems for trading signals
Your Skills & Talents
- PhD degree in Mathematics, Statistics, Physics, Computer Science, or another highly quantitative field
- Strong knowledge of probability and statistics (e.g., machine learning, time-series analysis, pattern recognition, NLP)
- Prior experience working in a data driven research environment
- Experience with NoSQL databases (e.g., MongoDB)
- Experience with distributed computing using MapReduce
- Experience with translating mathematical models and algorithms into code (Python, R or C++)
- Independent research experience
- Ability to manage multiple tasks and thrive in a fast-paced team environment
- Excellent analytical skills, with strong attention to detail
- Strong written and verbal communication skills
Opportunities available in London.
About Citadel Securities
Citadel Securities is the next-generation capital markets firm and a leading global market maker. We provide institutional and retail investors with the liquidity they need to trade a broad array of equity and fixed income products in any market condition. The brightest minds in finance, science and technology use powerful, advanced analytics to solve the market's most critical challenges, turning big ideas into real-world outcomes.
