At a Glance
- Tasks: Tackle complex NLP problems in finance using cutting-edge techniques and large language models.
- Company: Join G-Research, a leader in quantitative finance with a focus on innovation.
- Benefits: Enjoy competitive pay, 35 days off, and a relaxed dress code.
- Other info: Inclusive culture with great career growth and monthly company events.
- Why this job: Make a real impact by applying NLP to financial data and shaping future market predictions.
- Qualifications: Expertise in NLP, machine learning, and strong programming skills in Python required.
The predicted salary is between 60000 - 80000 £ per year.
We tackle the most complex problems in quantitative finance, bringing scientific clarity to financial complexity from our London HQ. The role involves working with very large text corpora, applying the latest NLP techniques and state‑of‑the‑art Large Language Models to identify real‑time text features that predict future market behaviour.
Qualifications
- Expert knowledge of Natural Language Processing or a related area of machine learning, via academic or industry experience (or both).
- Familiarity with recent advances in NLP and generative AI, including adapting LLMs to domain‑specific tasks such as Domain Adaptive Pre‑Training, Instruction Fine‑Tuning, quantisation and Low‑Rank Adaptation.
- Experience applying machine learning and deep learning methods to NLP tasks such as Text Embeddings, Sentiment Analysis, Named Entity Recognition, Knowledge Graphs, Multilingual Text and Topic Extraction.
- Demonstrated research excellence and a strong understanding of machine learning principles, algorithms and statistical methods.
- Excellent problem‑solving skills and the ability to work independently and as part of a team.
- Strong programming skills in Python and experience with ML libraries such as PyTorch or vLLM.
- Working towards or holding a Masters or PhD in NLP or a related quantitative field (machine learning, computer science, mathematics, statistics, physics or engineering).
- Publications at leading NLP conferences (ACL, EMNLP) and ML conferences (NeurIPS, ICML) are highly desirable.
- Interest in applying NLP concepts to real‑world financial data and implementing theoretical insights as working code.
- Strong communication skills, both written and verbal, are a plus.
- Previous financial experience is not required; interest in finance and a rapid learning mindset are prerequisite.
Benefits
- Highly competitive compensation plus annual discretionary bonus.
- Lunch provided (via Just Eat for Business) and dedicated barista bar.
- 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.
G‑Research is committed to cultivating and preserving an inclusive work environment. If you have a disability or special need that requires accommodation, please let us know in the relevant section.
Natural Language Processing Researcher in London employer: Braunford LLP
G-Research is an exceptional employer for a Natural Language Processing Researcher, offering a dynamic work environment in the heart of London where cutting-edge technology meets finance. With a strong emphasis on employee growth, competitive compensation, and a commitment to work-life balance, we provide our team with 35 days of annual leave, comprehensive healthcare, and opportunities for professional development. Our inclusive culture fosters collaboration and innovation, making it an ideal place for those passionate about applying NLP to real-world challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Natural Language Processing Researcher in London
✨Tip Number 1
Network like a pro! Reach out to folks in the NLP and finance sectors on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your NLP projects, especially those using Python and ML libraries. This gives us a tangible way to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on recent NLP advancements and be ready to discuss how they apply to real-world financial data. We love seeing candidates who are genuinely interested!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're keen on joining our team at G-Research.
We think you need these skills to ace Natural Language Processing Researcher in London
Some tips for your application 🫡
Show Off Your NLP Skills:Make sure to highlight your expertise in Natural Language Processing and any relevant machine learning experience. We want to see how you've tackled complex problems, so don’t hold back on sharing specific projects or techniques you've used!
Tailor Your Application:Customise your application to reflect the job description. Mention your familiarity with recent advances in NLP and generative AI, and how you can apply these to financial data. This shows us you're not just sending a generic application!
Demonstrate Your Research Excellence:If you've got publications at leading NLP or ML conferences, make sure to mention them! We love seeing evidence of your research excellence, so include links or references to your work if possible.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Braunford LLP
✨Know Your NLP Inside Out
Make sure you brush up on your knowledge of Natural Language Processing and the latest advancements in the field. Be ready to discuss specific techniques like Domain Adaptive Pre‑Training or Instruction Fine‑Tuning, as well as how you've applied them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of complex problems you've tackled using machine learning and deep learning methods. Highlight your experience with tasks like Sentiment Analysis or Named Entity Recognition, and be ready to explain your thought process in detail.
✨Demonstrate Your Programming Prowess
Since strong programming skills in Python are a must, be prepared to discuss your experience with ML libraries like PyTorch or vLLM. You might even want to bring along a code sample that showcases your ability to implement NLP concepts effectively.
✨Communicate Clearly and Confidently
Strong communication skills are a plus, so practice articulating your thoughts clearly. Whether it's discussing your research publications or explaining complex algorithms, being able to convey your ideas effectively will set you apart from other candidates.
