About the Role
<p><strong>Senior Data Scientist<br>Role type: Full time</strong></p><p class="MsoNormal"><strong>Location: UK (Fully Remote)</strong></p><p class="MsoNormal"><strong>Preferred start date: ASAP</strong></p><p class="MsoNormal"><br><strong>About Satalia</strong><br>Satalia builds enterprise-grade AI systems for WPP and its FTSE 100 client base. Led by WPP Chief AI Officer Daniel Hulme, we run as a high-autonomy, decentralised organisation where engineers and scientists own their domains end to end. We are building AI systems that operate on terabyte-scale multimodal datasets to power the next generation of marketing intelligence.</p><p class="MsoNormal"><br><strong>The Role</strong><br>Our current work includes:<br><strong>Agentic pipelines</strong> — multi-step LLM systems with tool use, planning, and self-evaluation that automate complex marketing workflows end to end.<br><strong>Domain-adapted foundation models</strong> — fine-tuning open-weight LLMs (LoRA, RLHF, distillation) on proprietary WPP data for tasks like audience segmentation, creative scoring, and brand-safety classification.<br><strong>Retrieval-augmented generation</strong> — production RAG systems over large proprietary corpora (embedding models, vector indices, re-ranking) that serve real-time answers to client queries.<br><strong>Classical ML at scale</strong> — gradient-boosted models, causal inference pipelines, and recommendation engines that run alongside LLM components in hybrid architectures.<br>You will be the technical lead for projects across these workstreams: scoping the problem, choosing the modelling approach, building the training and evaluation infrastructure, shipping to production, and iterating based on live metrics. You are not handing off a notebook to an engineering team — you ship what you build.</p><p class="MsoNormal"><br><strong>What You'll Do</strong><br>Design and run training pipelines — data curation, model selection, hyperparameter search, ablation studies — and be accountable for model quality on live traffic.<br>Build and maintain production inference services (latency budgets, batching strategies, quantisation, monitoring) that serve WPP's global client base.<br>Architect agentic AI systems: define tool schemas, orchestration logic, evaluation criteria, and failure modes for multi-step LLM workflows.<br>Work across the stack when needed — write the data pipeline, train the model, build the evaluation harness, deploy the service, and debug it when metrics drift.<br>Set technical direction for your workstream: write design docs, make build-vs-buy decisions, and defend your approach with evidence.<br>Mentor and set the quality standards for junior scientists.</p><p class="MsoNormal"><br><strong>What We're Looking For</strong><br>5+ years shipping ML models to production — you've dealt with data drift, silent failures,<br>retraining cadences, and the gap between offline metrics and business outcomes.<br>Deep, demonstrable expertise in at least one of: NLP/LLMs, computer vision, recommender systems, or causal inference.<br>Hands-on experience with LLM fine-tuning (LoRA, RLHF, DPO) or building LLM-powered<br>systems (agents, RAG, structured generation).<br>Strong software engineering habits — version control, testing, code review, CI/CD.<br>Comfort with ambiguity. Many of our problems don't have a known-good solution.<br>Clear communication — you can write a one-page design doc that is useful for both product managers and staff engineers.</p><p class="MsoNormal"><br><strong>Nice to Have</strong><br>Experience with multimodal models.<br>Background in marketing technology, ad tech, audience modelling, or media mix modelling.<br>Publications at top venues (NeurIPS, ICML, ACL, CVPR) or meaningful open-source<br>contributions.</p><p class="MsoNormal"><br><strong>What we Offer</strong></p><ul><li class="MsoNormal"><p><em>Benefits </em>- enhanced pension, life assurance, income protection, private healthcare;</p></li><li class="MsoNormal"><p><em>Remote working</em> - café, bedroom, beach - wherever works;</p></li><li class="MsoNormal"><p><em>Truly flexible working hours </em>- school pick up, volunteering, gym;</p></li><li class="MsoNormal"><p><em>Generous Leave </em>- 27 days oliday plus bank holidays and enhanced family leave;</p></li><li class="MsoNormal"><p><em>Annual bonus</em> - when Satalia does well, we all do well;</p></li><li class="MsoNormal"><p><em>Impactful projects</em> - focus on bringing meaningful social and environmental change;</p></li><li class="MsoNormal"><p><em>People oriented culture</em> - wellbeing is a priority, as is being a nice person;</p></li><li class="MsoNormal"><p><em>Transparent and open culture</em> - you will be heard;</p></li><li class="MsoNormal"><p><em>Development </em>- focus on bringing the best out of each other;</p></li></ul><p class="MsoNormal">Satalia is home to some of the brightest minds in AI and if you’re looking to join a company who not only values autonomy and freedom, but embraces a culture of inclusion and warmth, we’d love to hear from you.</p><p class="MsoNormal">We aim to respond to all applications within 2 weeks. If you have not heard from us within 2 weeks this means your application has been unsuccessful.<br><br>By applying to Satalia you are expressly giving your consent for the collection and use of your information as described within our <a target="_blank" href="https://careers.satalia.com/privacy_policy">Satalia Recruitment Privacy Policy</a>. <br><br>Good luck!</p><p class="MsoNormal"></p>