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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 real-world text data across tasks such as classification, extraction, embeddings, or search — at a meaningful scale. - Some exposure to instruction fine-tuning or model serving, with an interest in going deeper. - A grounding in classical ML and statistics, and the instinct to reach for simpler methods when warranted. - Familiarity with GenAI and agentic patterns, even if hands-on production experience is still developing. - Clear communication skills and the ability to explain technical work to colleagues across functions. - Genuine curiosity about AI and a habit of experimenting — you learn by doing. - Good ownership instincts: you follow problems through rather than passing them on. ➕It would be a bonus if you: - MSc in Computer Science, Machine Learning, AI, Data Science, Computational Linguistics, or a closely related STEM field. 🔎 Our Hiring Process 1. Let’s introduce ourselves – you’ll complete an introductory asynchronous interview - we’d love to learn more about you, your ambitions, and what you’re looking for in your next step. 2. Get to know your would-be manager – you’ll have a call with Aji, our Chief Scientist, to learn more about the role and show off your experience. 3. Show us how you work – you'll complete a short take home assignment 4. Get to know your would-be team – You'll meet a mix of people who you'll be working closely with from the Data Science, Engineering and Product teams. 5. How our values and your caree