Quantitative Trader / Researcher - EMEA

Tower Research Capital·London, Paris, Amsterdam·onsite
finance:systematicquant-researchIC4Quantitative Research & Trading
Compensation
Not disclosed
Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities. Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization. Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance. At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best. At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. As a member of one of Tower’s trading teams, a Quantitative Trader / Researcher will be using Tower’s in-house trading system—one of the fastest and most comprehensive in the world—to develop and deploy algorithmic trading strategies based on patterns in market behavior. Responsibilities Designing, implementing, and deploying trading algorithms Researching high to mid frequency alphas Exploring trading ideas by analysing market data, market micro-structure and alternate dat