Quantitative Researcher: Europe Tactic Specialist - Two Sigma Securities UK
London, United Kingdom of Great Britain and Northern Ireland
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Two Sigma is a financial sciences company, combining data analysis, invention, and rigorous inquiry to help solve the toughest challenges in investment management, insurance technology, securities, private equity, and venture capital. Our team of scientists, technologists, and academics looks beyond the traditional to develop creative solutions to some of the world’s most complex economic problems.
Two Sigma Securities brings a scientific approach to systematic trading and risk management to make markets more efficient. Our team trades over 10,000 US equities and 4,000 listed options, leveraging our high performance trading system to execute over 850 million shares per day. Two Sigma Securities is entering an exciting growth phase. We value the insights of our colleagues and encourage them to innovate and shape their own work agenda. From building next generation trading technologies and researching novel AI and machine learning techniques to enhancing our strategies and deploying automation, our team is pushing the frontier in systematic trading.
We are seeking an experienced quantitative researcher to join our Market Making & Intraday Alpha (MMIA) team in London to develop new tactics leveraging our high performance proprietary trading platform across futures, ETFs and equities products. Ideal candidates will have industry experience researching, developing, testing, and deploying systematic short-horizon trading strategies, with a particular focus across European futures and equity markets to increase volumes traded and business profitability.
You will take on the following responsibilities:
- Systematically analyze market data to discover underlying patterns from historical market movement leveraging cutting edge computing techniques (e.g. Machine Learning, Artificial Intelligence, etc.)
- Design, implement and manage equities and futures trading strategies that identify microstructure inefficiencies, and defragment liquidity across global exchanges on the existing TSS high frequency trading platform
- Continuously test and enhance existing strategies to expand region profitability
- Develop, maintain, and enhance the HFT research platform for quantitative researchers in the team, by augmenting capabilities including our simulation engine, feature generation, and forecast evaluation tools
- Provide solid statistical analysis to drive key business decisions such as expansion into additional international futures and equities markets and additional strategies.
- Work with engineering partners to drive performance improvements to our proprietary ultra-low latency trading platform
You should possess the following qualifications:
- 5+ years’ experience working in a quantitative discipline or research environment in European or global securities markets
- Degree in Computer Science, Mathematics, or related Stem field
- Demonstrated knowledge of advanced algorithms and data science techniques
- Technical aptitude for large scale data analysis
- Knowledge of scripting languages such as Python and Bash
- Programming skills in developing high-performance, multi-threaded applications in Linux environment
- Experience with databases
- Experience with version control systems, including Git and Mercurial
- Experience with building large-scale, real-time and distributed applications
- Advanced programing skills in at least one programing language (C, C++ preferred)
- Experience performing an in-depth research project leveraging real-world time-series data, experience with using Python preferred
- Ability to think independently and creatively approach data analysis and communicate complex ideas clearly
We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.