G

G-Research

Quantitative finance research applying rigorous methods

Natural Language Processing Intern

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Internship · Summer 2027London, UK

About the Job

Requirements

  • A postgraduate degree in Natural Language Processing or a related discipline, or equivalent commercial experience developing novel machine learning algorithms, is required; exceptional candidates with a strong track record in data science competitions such as Kaggle will also be considered.
  • Experience working with large-scale, noisy text datasets and building models for information extraction, sentiment analysis, or semantic understanding is required.
  • Strong Python programming skills and experience using modern machine learning frameworks such as PyTorch or TensorFlow are required.
  • Strong mathematical and problem-solving skills, including the ability to develop novel models where standard approaches are insufficient, are required.
  • An interest in finance and a willingness to learn are required.

Responsibilities

  • Investigate foundational questions, uncover market insights, and push the boundaries of quantitative research with support from large-scale computing resources.
  • Apply innovative mathematical and computational analysis to a meaningful research project in natural language processing.
  • Work on direct, production-ready applications using tools and techniques in an applied setting.
  • Present research ideas to senior management at the conclusion of the internship.

Desired Qualifications

  • A PhD is preferred.
  • Publications at leading natural language processing or machine learning conferences such as ACL, EMNLP, NAACL, NeurIPS, or ICML are advantageous.

About the Company

G-Research

Quantitative finance research applying rigorous methods

G-Research applies scientific rigour to solve complex challenges in financial markets. It brings together world-class researchers and engineers to develop data-driven models and trading ideas, testing them through rigorous experimentation and robust infrastructure. Unlike many traditional asset managers, its culture emphasizes deep exploration, reproducibility, methodical execution, and long-term thinking. The goal is to generate alpha through disciplined, evidence-based research that informs investment decisions and advances understanding of financial markets.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2001

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