Senior quantitative researcher - machine learning trading

We are expanding our research organization and are looking for an experienced Senior Quantitative Researcher to join our Amsterdam-based team. This position plays a key role in shaping new research initiatives and carries responsibility for technical leadership, mentorship, and team development.

In this role, you will work on the discovery and productionization of machine-learning-driven trading strategies, while helping guide junior researchers and collaborating closely with trading, engineering, and infrastructure teams.

Your role

• Creating, testing, and deploying machine-learning-based statistical arbitrage strategies in live trading environments
• Identifying new sources of alpha through deep analysis of high-frequency market data
• Developing features and predictive models across large universes of instruments over short-term horizons (seconds to minutes)
• Building and maintaining scalable ML research and production pipelines across multiple venues and markets
• Continuously improving existing models through rigorous evaluation and optimization
• Acting as a key point of contact between research, trading, and engineering groups
• Providing technical guidance, mentorship, and-where appropriate-line management to other researchers

• Five or more years of hands-on experience in a high-frequency or ultra-low-latency trading environment

• Strong track record applying machine learning techniques to systematic trading strategies

• Practical experience operating ML pipelines across multiple exchanges, both independently and in coordinated setups

• Demonstrated ability to design and implement complex statistical arbitrage strategies across multiple instruments

• Willingness to deepen expertise in high-frequency market dynamics and scale strategies across many trading venues

• End-to-end ownership mindset, from raw data ingestion and feature engineering through to live deployment

• Strong programming skills in at least one language; Python experience preferred

• A self-driven, resilient, and highly engaged approach to problem solving

• Ability to collaborate effectively with colleagues from diverse technical and academic backgrounds Nice to have

• Prior experience mentoring researchers, supervising interns, or leading small quantitative team