Data Scientist

Stack

Responsibilities

• ▹Train, evaluate, and iterate on ML models for customer feedback tasks, contributing to custom fine-tuning pipelines
• ▹Build and maintain LLM-powered features including retrieval pipelines, reranking systems, and insight generation, with support from senior team members
• ▹Contribute to evaluation frameworks: 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
• ▹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
• ▹Stay close to relevant research and bring useful ideas from the literature into team discussions

Requirements

• ▹Solid working knowledge of transformer architectures and their application in NLP tasks
• ▹Proficiency in PyTorch, including training loops and standard model fine-tuning workflows
• ▹Experience working with real-world text data across classification, extraction, embeddings, or search at a meaningful scale
• ▹Some exposure to instruction fine-tuning or model serving
• ▹A grounding in classical ML and statistics, with the instinct to reach for simpler methods when warranted
• ▹Familiarity with GenAI and agentic patterns
• ▹Clear communication skills, able to explain technical work across functions
• ▹Genuine curiosity about AI and a habit of experimenting
• ▹Good ownership instincts, following problems through rather than passing them on

Nice to have

• ▹MSc in Computer Science, Machine Learning, AI, Data Science, Computational Linguistics, or a closely related STEM field

Soft skills

What we offer

• ▹Flexible working in a choice-first environment
• ▹Work-from-home allowance
• ▹25 days holiday + local bank holidays, plus an extra day per year of service
• ▹Your birthday off
• ▹Annual learning & development budget
• ▹Equity options
• ▹Monthly health & wellbeing budget
• ▹Optional private healthcare plan
• ▹Life assurance & income protection (location dependent)
• ▹Employee Assistance Programme (location dependent)
• ▹Enhanced family, fertility and neonatal leave
• ▹Dog-friendly London office with events and rooftop terrace

About the company

Chattermill's mission is to help large successful brands like Uber, Amazon, Wise, and HelloFresh put their customers at the centre of everything they do. Its Customer Experience Intelligence platform continuously analyses explicit and implicit feedback using custom models specialised for customer feedback.