Quantitative Research Analyst Machine Learning

A leading quantitative investment firm is hiring a Quantitative Research Analyst to develop machine-learning-driven equity signals. This is a research seat for someone who builds predictive signals from rich and unconventional data and turns them into investable alpha.

The role

1. Develop cross-sectional equity signals using machine-learning methods across global regions
2. Engineer signals from alternative data — and apply NLP / LLM-based text analysis to corporate disclosures and other sources
3. Enhance and diversify multi-factor signal libraries, with a focus on low-correlation, downside-protective ideas
4. Monitor signal performance, benchmark against historical distributions, and support ad hoc analytics

You will have

1. An advanced degree (MFE, MS, or PhD) in a quantitative discipline
2. Around 2–4 years in quantitative equity research (exceptional recent graduates considered)
3. Strong Python (pandas, scikit-learn, XGBoost) and machine-learning fluency; R a plus
4. Hands-on experience with factor research, alternative data, and point-in-time datasets

Why apply

A research-led environment where strong ideas get backed and your signals reach live portfolios. Highly competitive compensation.