Natural Language Processing Researcher
2 days ago
We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.
From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.
Join a research team where curiosity meets scale. G-Research is seeking a Natural Language Processing (NLP) Researcher to join a successful, experienced and growing research group.
Alongside NLP experts and quantitative researchers, you will work on very large text corpora, using the latest NLP techniques and state of the art Large Language Models (LLM), with the goal of identifying features of real time text feeds that can we used to predict the future behaviour of financial markets.
Expert knowledge of Natural Language Processing or a related area of machine learning, through academic or industry experience (or both)
Experience applying machine learning and deep learning methods to a range of NLP-related tasks, such as Text Embeddings, Sentiment Analysis, Named Entity Recognition, Knowledge Graphs, Multilingual Text and Topic Extraction
A proven track record of research excellence and a deep understanding of machine learning principles, algorithms and statistical methods.
Strong programming skills in Python and experience with machine learning libraries such as PyTorch, vLLM or similar are a prerequisite
You will have, or be working towards gaining, a Masters or PhD degree in NLP or a related quantitative subject, such as machine learning, computer science, mathematics, statistics, physics or engineering
An interest in applying NLP concepts to real world financial data and implementing theoretical insights as working code
Previous financial experience is not required, although interest in finance and the motivation to rapidly learn more is a prerequisite for working here
Highly competitive compensation plus annual discretionary bonus
~ 35 days’ annual leave
~9% company pension contributions
~ Informal dress code and excellent work/life balance
~ Comprehensive healthcare and life assurance
~ Cycle-to-work scheme
~ Monthly company events
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