Data Scientist

🕒 il y a 2 mois

🇬🇧 Royaume-Uni – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

📊 Data Scientist

🇬🇧 Parrain de Visa de Travailleur Qualifié UK

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👻 Score fantôme 33%

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🗣️🇺🇸🇬🇧 Anglais requis

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Logo of Chattermill

Chattermill

51 - 200 employés

Fondée en 2015

🤖 Intelligence artificielle

☁️ SaaS

🤝 B2B

💰 €26 000 000 Series B - Chattermill en 2022-12

Artificial Intelligence • SaaS • B2B

Chattermill est une plateforme d'intelligence de l'expérience client (CX) qui unifie les retours d'enquêtes, d'avis, de tickets de support, de réseaux sociaux et d'appels vocaux, et applique l'IA pour révéler des insights prioritaires et fondés sur des preuves. Ses analyses alimentées par l'IA étiquettent, regroupent et résument automatiquement les retours non structurés afin que les équipes CX, Produit et Support puissent diagnostiquer les causes profondes, prioriser les corrections et mesurer l'impact sur des indicateurs tels que le NPS et le CSAT. La plateforme est proposée comme un produit SaaS cloud pour les équipes centrées sur le client et les entreprises.

Description

• 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.

🎯 Exigences

• 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.

🏖️ Avantages

• Flexible working in a choice-first environment - we trust the way you want to work! • Work-from-home allowance to set up your ideal workspace • 25 days holiday + local bank holidays, plus an extra day for each year of service • Your birthday off • Annual learning & development budget to support your growth (increasing over time) • Equity options — share in the company’s success • Monthly health & wellbeing budget, increasing with length of service • Optional private healthcare plan • Life assurance & income protection (location dependent) • Employee Assistance Programme (location dependent) for extra support when you need it • Enhanced family leave (location dependent), plus fertility and neonatal leave • If you’re in London, a dog-friendly office with great classes, events, and a rooftop terrace

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