Machine Learning Researcher
Location: Amsterdam / Remote
Our client is a rapidly growing proprietary trading firm specialising in systematic trading and market-making across global futures markets. Combining a research-first culture with significant investment in technology and infrastructure, the firm empowers researchers to take ownership of ideas and directly influence trading performance. As the business continues to expand, they are seeking an exceptional Machine Learning Researcher to develop next-generation quantitative trading strategies and contribute to the firm's long-term research agenda.
The Opportunity
This is an opportunity to join a highly collaborative team at the intersection of machine learning, quantitative research, and systematic trading. You will work alongside experienced Quant Researchers, Traders, and Technology teams to identify alpha opportunities, build predictive models, and deploy research into live production environments.
The ideal candidate will have a strong academic background in machine learning or a related quantitative field, alongside a demonstrated track record of high-quality research through leading publications, competitive internships, or industry experience.
Responsibilities
- Conduct cutting-edge machine learning research for systematic trading and market-making strategies
- Develop predictive models using large-scale financial, market microstructure, and alternative datasets
- Generate, evaluate, and refine alpha signals across global futures and other liquid markets
- Collaborate closely with Quant Researchers, Traders, and Portfolio Managers to translate research into production strategies
- Build and enhance research infrastructure, modelling frameworks, and data pipelines
- Analyse large and complex datasets to extract meaningful insights and uncover inefficiencies
- Present research findings and recommendations to both technical and non-technical stakeholders
- Stay at the forefront of developments in machine learning, artificial intelligence, and quantitative finance
Requirements
- PhD or Master's degree in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering, or another highly quantitative discipline
- Strong foundation in machine learning, statistical modelling, optimisation, and predictive analytics
- Excellent Python programming skills with experience working in research environments
- Experience handling and analysing large-scale datasets
- Ability to thrive in a fast-paced, highly collaborative environment
Preferred Background
Candidates are particularly encouraged to apply if they possess one or more of the following:
- Publications at leading machine learning or AI conferences, including NeurIPS, ICML, ICLR and AISTATS
- Internship or full-time experience at a leading proprietary trading firm, hedge fund, quantitative trading company, or top-tier technology firm
- Academic background from a leading European or global university with a strong reputation in quantitative research and machine learning
- Experience applying machine learning techniques to real-world prediction, optimisation, or decision-making problems
- Exposure to financial markets, quantitative research, algorithmic trading, or market-making environments
