Data Scientist

Job description

Data Scientist 🌍 UK (Remote or Hybrid, it’s up to you!) 💰 Dependent on experience 📈 Be part of our success with the opportunity to join our company equity scheme 🦸‍♀️ The Role 🦸‍♀️ Our mission is to help large successful brands like Uber, Amazon, Wise, HelloFresh (and more!) put their customers at the centre of everything they do. Using best-in-class tech in a fast-developing AI space, our Customer Experience Intelligence platform continuously analyses explicit and implicit feedback to enable our clients to identify what they should do next. We're hiring a Data Scientist to join the team and help build and ship the next generation of that stack. 👉 What you'll be doing: Unlike many companies, we use our own custom models, specialised for customer feedback, across various parts of the stack: extraction, retrieval, reranking, summarisation, and sentiment analysis. We are also pragmatic and understand that the right solution can be a combination of off-the-shelf LLMs, bespoke fine-tuned models, and sometimes techniques that utilise no LLM at all. This means you will: Train, evaluate, and iterate on ML models for customer feedback tasks, contributing to our custom fine-tuning pipelines and running experiments with rigour and clear documentation. Build and maintain LLM-powered features including retrieval pipelines, reranking systems, and insight generation — with support and guidance from senior team members. Contribute to evaluation frameworks: help build test sets, define metrics, and assess model quality across classification, extraction, and generative tasks. Work on semantic search and retrieval, developing a strong working understanding of embedding-based approaches and the methods that go beyond them. Write clean, well-tested code and collaborate with Engineering on model integration, data pipelines, and monitoring. Work with the wider Data Science team to translate business and product requirements into practical ML experiments and solutions. Stay close to relevant research and bring useful ideas from the literature into team discussions and experiments. 🧰 What you’ll need: A solid working knowledge of transformer architectures and how they are applied in NLP tasks. Proficiency in PyTorch, including training loops and standard model fine-tuning workflows; exposure to parameter-efficient techniques such as LoRA is a plus. Experience working with re…