Machine Learning Quantitative Researcher

Base pay range

$200,000.00/yr - $300,000.00/yr

About the role

A leading proprietary trading firm is seeking a Machine Learning Quantitative Researcher to join its systematic trading team. In this role, you’ll design and deploy advanced machine learning models — from NLP-driven signals to graph-based time series models — with the goal of generating alpha in global equities and futures markets.

This is an outstanding opportunity to apply your research at scale, working with world-class researchers, traders, and engineers in a fast-paced, collaborative environment where your models directly impact trading performance.

Key responsibilities

• Research, design, and implement novel trading signals using machine learning, NLP, and deep learning .
• Conduct large-scale data analysis, backtesting, and scenario simulations to validate robustness and stability.
• Build production-grade ML pipelines , including retraining, drift detection, and real-time monitoring.
• Apply advanced architectures such as transformers, attention models, and graph neural networks to financial time series and cross-asset datasets.
• Collaborate with engineering and trading teams to optimize infrastructure and ensure seamless execution.

Requirements

• Minimum 3 years of experience applying machine learning in systematic trading, alpha signal generation, or predictive modeling.
• Advanced degree (PhD or Master’s) in a quantitative or technical discipline (statistics, mathematics, computer science, engineering, physics).
• Strong programming expertise in Python and C++ , with proven ability to productionize models.
• Experience with transformers, reinforcement learning, or GNNs applied to time series/financial data.
• Solid understanding of market microstructure and intraday trading dynamics.
• Excellent problem-solving skills and the ability to thrive in a collaborative, high-performance environment.

What’s on offer

• The chance to apply state-of-the-art machine learning research directly to live trading strategies.
• Highly competitive compensation with performance-based bonuses.
• An intellectually challenging, collaborative culture where innovation directly drives results.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Research and Engineering

Industries

• Financial Services and Capital Markets

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