Senior Data Scientist
Role type: Full time

Location: UK (Fully Remote)

Preferred start date: ASAP

About Satalia
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.

The Role
Our current work includes:
Agentic pipelines — multi-step LLM systems with tool use, planning, and self-evaluation that automate complex marketing workflows end to end.
Domain-adapted foundation models — fine-tuning open-weight LLMs (LoRA, RLHF, distillation) on proprietary WPP data for tasks like audience segmentation, creative scoring, and brand-safety classification.
Retrieval-augmented generation — production RAG systems over large proprietary corpora (embedding models, vector indices, re-ranking) that serve real-time answers to client queries.
Classical ML at scale — gradient-boosted models, causal inference pipelines, and recommendation engines that run alongside LLM components in hybrid architectures.
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.

What You'll Do
Design and run training pipelines — data curation, model selection, hyperparameter search, ablation studies — and be accountable for model quality on live traffic.
Build and maintain production inference services (latency budgets, batching strategies, quantisation, monitoring) that serve WPP's global client base.
Architect agentic AI systems: define tool schemas, orchestration logic, evaluation criteria, and failure modes for multi-step LLM workflows.
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.
Set technical direction for your workstream: write design docs, make build-vs-buy decisions, and defend your approach with evidence.
Mentor and set the quality standards for junior scientists.

What We're Looking For
5+ years shipping ML models to production — you've dealt with data drift, silent failures,
retraining cadences, and the gap between offline metrics and business outcomes.
Deep, demonstrable expertise in at least one of: NLP/LLMs, computer vision, recommender systems, or causal inference.
Hands-on experience with LLM fine-tuning (LoRA, RLHF, DPO) or building LLM-powered
systems (agents, RAG, structured generation).
Strong software engineering habits — version control, testing, code review, CI/CD.
Comfort with ambiguity. Many of our problems don't have a known-good solution.
Clear communication — you can write a one-page design doc that is useful for both product managers and staff engineers.

Nice to Have
Experience with multimodal models.
Background in marketing technology, ad tech, audience modelling, or media mix modelling.
Publications at top venues (NeurIPS, ICML, ACL, CVPR) or meaningful open-source
contributions.

What we Offer

• Benefits - enhanced pension, life assurance, income protection, private healthcare;

• Remote working - café, bedroom, beach - wherever works;

• Truly flexible working hours - school pick up, volunteering, gym;

• Generous Leave - 27 days oliday plus bank holidays and enhanced family leave;

• Annual bonus - when Satalia does well, we all do well;

• Impactful projects - focus on bringing meaningful social and environmental change;

• People oriented culture - wellbeing is a priority, as is being a nice person;

• Transparent and open culture - you will be heard;

• Development - focus on bringing the best out of each other;

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.

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.

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Good luck!