At a Glance
- Tasks: Tackle complex NLP problems in finance using cutting-edge techniques and large language models.
- Company: Join a leading quantitative finance firm based in London with a collaborative culture.
- Benefits: Highly competitive salary, annual bonus, 35 days leave, and comprehensive healthcare.
- Other info: Enjoy a flexible work environment with monthly events and a focus on inclusivity.
- 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 employer: Braunford LLP
At G-Research, we pride ourselves on being an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets finance. Our commitment to employee growth is evident through our competitive compensation, extensive annual leave, and a culture that promotes work/life balance, alongside opportunities for professional development in cutting-edge NLP research. With a focus on inclusivity and a vibrant team atmosphere, we ensure that every employee feels valued and empowered to contribute to solving complex financial challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Natural Language Processing Researcher
✨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 taste of what you can do beyond the application.
✨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 excited about the field!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate individuals who want to tackle complex problems with us.
We think you need these skills to ace Natural Language Processing Researcher
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!
Keep It Clear and Concise:We appreciate clarity! Make sure your application is well-structured and easy to read. Use bullet points where necessary and avoid jargon unless it’s relevant to the role. We want to understand your skills without getting lost in the details.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Braunford LLP
✨Know Your NLP Inside Out
Make sure you brush up on the latest NLP techniques and state-of-the-art Large Language Models. Be ready to discuss how you've applied these in your past work or research, especially in relation to tasks like Text Embeddings or Sentiment Analysis.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex problems you've tackled using machine learning principles. Think about how you approached these challenges and what algorithms or statistical methods you employed to find solutions.
✨Demonstrate Your Programming Prowess
Since strong programming skills in Python are a must, be ready to talk about your experience with ML libraries like PyTorch or vLLM. You might even want to prepare a small coding example or two that showcases your skills.
✨Express Your Interest in Finance
Even if you don't have direct financial experience, show your enthusiasm for applying NLP concepts to real-world financial data. Discuss any relevant projects or ideas you have that bridge the gap between NLP and finance.
