Machine Learning Quantitative Researcher

Evolve Inc
New York, NY, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$200,000 - $300,000
Working hours
Regular working hours
Job source

Tech stack

Big Data C++ (Programming Language) Python (Programming Language) Machine Learning Natural Language Processing Reinforcement Learning Graph Neural Networks Deep Learning Information Technology Machine Learning Operations

Job description

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., * 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.

Benefits & conditions

  • 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.

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