Senior Research Engineer
Flow Traders is a global liquidity provider that delivers continuous liquidity in financial markets, with deep expertise in Exchange Traded Products (ETPs). The firm lowers overall trading costs for market participants by providing higher execution quality across global exchanges and trading platforms.
About Flow Traders
Flow Traders is a technology-driven liquidity provider operating in global financial markets, with a particular focus on Exchange Traded Products (ETPs). The company combines deep ETP expertise, cutting-edge technology, and strong risk management to increase transparency and efficiency across the financial ecosystem, serving market participants such as exchanges and trading platforms across Europe, the U.S. and Asia-Pacific. Beyond its core trading business, Flow Traders operates a dedicated strategic capital investment unit that partners with companies aligned to its mission of transparency and efficiency in financial markets, and it runs the Flow Traders Foundation, a philanthropic initiative focused on fighting poverty.
Skills
About the Role
You will help lead the development of our trading model research framework and use it to conduct research to develop models for trading in production. You'll expand the framework to become the global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.
Requirements
- Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
- 8+ years of hands-on experience in MLOps, Research Engineering, or ML Research
- A strong background in mathematics and statistics
- Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray
- Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
- Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
- Understanding of cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes)
Responsibilities
- Help lead the development and global rollout of the research framework for defining and training models through various optimization procedures such as supervised learning and backtesting
- Integrate the research framework with the platform for deploying and running models in production
- Partner with Quantitative Researchers to conduct research
- Test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals