What are the responsibilities and job description for the Quantitative Researcher position at HWTS Global?
Quant Researcher (Machine Learning – Equities) | London / New York | Multi-Strategy Platform
We’re partnering with a top-tier multi-strategy hedge fund looking to hire an Equity Quant Researcher with a strong ML focus. This role sits within a high-performing systematic equities team, focused on building scalable, data-driven alpha using modern machine learning techniques.
The team operates in a fast-paced, performance-led environment with strong infrastructure and access to diverse datasets. You’ll be working closely with experienced PMs and researchers to push forward next-generation equity signals.
What You’ll Be Doing
- Design and develop machine learning-driven alpha signals for systematic equity strategies
- Work with large, complex datasets to extract predictive features and insights
- Take ownership of the full research lifecycle: ideation, testing, validation, and deployment
- Collaborate with PMs to translate research into live trading strategies
- Continuously refine models with a focus on robustness, scalability, and real-world performance
- Contribute to the evolution of the team’s research framework and data infrastructure
Core Requirements
- 5 years’ experience in systematic equity research with a track record of deployable alpha generation
- Strong intuition for market dynamics, including liquidity, participant behaviour, and changing risk regimes
- Advanced Python programming skills, with experience in research and production environments
- Deep experience working with core financial datasets (e.g. prices, fundamentals, risk factors)
- Proven ability to handle large, imperfect datasets and navigate real-world data challenges
- Strong understanding of backtesting frameworks and common pitfalls (e.g. overfitting, look-ahead bias, transaction costs)
- Excellent academic background in a quantitative field
Nice to Have
- Experience working with high-frequency or granular (tick-level) equity data
- Hands-on application of machine learning techniques (e.g. tree-based models, deep learning, NLP/LLMs) in alpha research
- Familiarity with market microstructure in developed equity markets
- Exposure to C or performance-focused programming
Why This Role
- Work within a well-resourced, high-performing multi-strat platform
- Access to cutting-edge data and compute infrastructure
- Strong emphasis on ML-driven research and innovation
- Direct path to impactful alpha generation and deployment
- Locations: London or New York
Salary : $400,000 - $900,000