My client is a research-driven quantitative trading firm operating continuously across global markets. Their edge comes entirely from systematic models, not intuition, and their researchers own the full stack: hypothesis, signal, backtest, implementation, and live trading. If your work is good, it goes live. If it doesn't perform, you find out why and fix it.
What you'll be working on:
- Developing alpha-generating signals and pricing models for ETF and index-related strategies
- Analysing market microstructure: quote dynamics, liquidity, intraday flows, and passive rebalancing mechanics
- Working with large-scale tick data to identify and exploit structural inefficiencies in exchange-traded products
- Improving execution models and understanding cross-asset hedging relationships
What they are looking for:
- Strong quantitative background (PhD or equivalent research experience in mathematics, statistics, physics, computer science, or a related field)
- 3+ years of applied experience in a systematic trading or quantitative research environment
- Comfort with the full research lifecycle, from data wrangling to live deployment
- Solid programming skills in Python and/or C++; experience with large financial datasets
- Genuine understanding of ETF mechanics, index arbitrage, or market microstructure (not just passing familiarity)
What this is not:
- A sales or structured products role
- A "quant" title with a trader making the calls above you
- A firm where research output gets lost in committee
What you get:
A small, senior, collaborative team where your research directly determines what they trade. Minimal meetings. High standards. The infrastructure and data to do the work properly.
If you have a meaningful track record in systematic ETF research or market making and want to understand what they're building, reach out.