We are partnering with a leading multi-manager investment platform to hire a Machine Learning Quant Researcher (0-4 years' experience) into a high-performing equity statistical arbitrage pod based in Zug. This is a rare opportunity to join a lean, highly collaborative team with a strong research culture and direct impact on live trading strategies.
The team operates within a fast-paced, performance-driven environment but maintains an entrepreneurial, close-knit feel, offering significant ownership and visibility from day one. The role sits at the intersection of machine learning, quantitative research, and alpha generation, working closely with the Portfolio Manager and broader team to develop and deploy signals.
Key Responsibilities
- Research, develop, and refine machine learning-driven alpha signals for equities stat arb strategies
- Work with large, high-dimensional datasets to extract predictive features and signals
- Apply advanced ML techniques (e.g. supervised/unsupervised learning, time series modelling) to improve signal quality
- Collaborate closely with PMs and researchers to translate research into live trading strategies
- Conduct rigorous backtesting and performance analysis, with a focus on robustness and scalability
- Continuously iterate on models to improve Sharpe, capacity, and execution efficiency
Candidate Profile
We are targeting high-calibre, intellectually strong individuals with excellent academic backgrounds and a demonstrated interest in quantitative finance and/or ML research. Suitable profiles may include:
- Top MSc graduates (e.g. Oxbridge, Imperial, ETH, EPFL, top French schools) with internships in hedge funds, banks, or leading tech firms
- PhD graduates in Machine Learning, Statistics, Mathematics, or Computer Science (no prior finance experience required)
- Junior Quant Researchers from banks or hedge funds with up to ~4 years' experience
- Early-career ML Researchers/Engineers from tech or finance with a strong theoretical foundation and interest in markets
Requirements
- 0-4 years' experience in a relevant field (quant research, ML, data science, or similar)
- Strong programming skills (Python essential; C++ beneficial)
- Solid grounding in statistics, machine learning, and data analysis
- Excellent problem-solving ability and intellectual curiosity
- Strong academic pedigree from a top-tier university
- Ability to thrive in a collaborative, high-performance environment
Additional Information
- Location: Zug (on-site)
- Team: Small, collaborative equity stat arb pod
- Headcount: 2 hires (ML-focused & traditional QR)
- Flexibility: Open to waiting for top candidates (including up to ~1 year in exceptional cases)
This is an excellent opportunity for a junior researcher to join a genuinely meritocratic environment, work on high-impact alpha research, and accelerate their career within one of the most competitive areas of systematic trading.
