Define alpha generation, model risk, and research-to-production processes. Design ML-based experiments, build research pipelines, and develop trading strategies. Collaborate with engineering and data teams.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Our client is building a new systematic trading research team from the ground up — applying machine learning and quantitative methods to the markets.
As their first Quantitative Researcher, you’ll define how we generate alpha, model risk, and bring research from theory to production. This is a hands-on role where creativity meets scientific rigor.
What You’ll Do
- Design and run ML-based experiments to identify predictive features and robust models
- Explore academic and industry research to inspire new approaches to signal generation and portfolio construction
- Build and document structured, reproducible research pipelines with clear hypotheses and testing cycles
- Collaborate with engineering and data teams to implement models and features in a production environment
- Develop robust risk-aware trading strategies using advanced ML and statistical techniques
- Contribute to shaping the long-term research agenda and team processes
About You
You’re driven by curiosity, data, and structure — with the mindset of a scientist and the instincts of a problem-solver.
You bring:
- MSc or PhD in a quantitative field (Mathematics, Statistics, Computer Science, Finance) STEM
- 1+ year in quantitative research or systematic trading
- Strong Python skills (NumPy, pandas, PyTorch)
- Solid understanding of probability, statistics, and model evaluation
- Experience translating academic research into practical modeling approaches
- A structured approach — plan first, test methodically, and document clearly
Why Join
You’ll help define the research culture from day one — setting the standard for how to test ideas, evaluate uncertainty, and build trading systems.
If you’re excited by the idea of building something new — and doing it right from the start — they’d love to hear from you.
Based in Denmark, relocation from anywhere welcome.