Quantitative Researcher

XTX Markets is a leading global electronic market maker, established with the mission to revolutionise trading through the use of technology and advanced mathematical models. Headquartered in London, XTX Markets specialises in providing liquidity across a variety of asset classes, including equities, foreign exchange, fixed income, and commodities. By combining quantitative research and state-of-the-art technology, XTX identifies and executes trading opportunities with efficiency and precision, contributing to more liquid and efficient markets worldwide. The cornerstone of XTX Markets' success is its investment in technology and data analytics, enabling the firm to analyse vast amounts of market data in real time. This capability allows XTX to deploy complex algorithms and trading strategies that adapt to market conditions, setting it apart from traditional market participants. The firm's team comprises highly skilled individuals from diverse backgrounds, including data science, software engineering, and finance, fostering an environment of innovation and collaboration. XTX Markets is committed to a principle of fairness and transparency in the financial markets, advocating for practices that benefit the broader market ecosystem. The firm also places a strong emphasis on corporate social responsibility, actively engaging in philanthropic efforts and initiatives aimed at improving education and reducing environmental impact. With its cutting-edge approach to electronic market making, XTX Markets has emerged as a key player in the global financial landscape, driving forward the integration of technology and finance. The firm's dedication to innovation, ethical trading practices, and social responsibility underscores its unique position in the industry, as it continues to set new standards for excellence in market making.

• Degree in math, physics, computer science or another quantitative field
• Strong evidence of ability to conduct original research
• Demonstrated practical experience of, or deep understanding of, modern deep learning architectures
• Good knowledge of other machine learning techniques and statistics
• Solid programming skills (language does not matter)
• Track record of solving practical and analytical problems
• Outstanding performance in any quantitative field or contest preferred (Kaggle, hackathons, olympiads, academic contests etc)
• Experience implementing machine learning algorithms in industry (preferred)