At a Glance
- Tasks: Lead innovative AI projects and design cutting-edge machine learning models.
- Company: Join Satalia, a pioneering AI company transforming marketing intelligence.
- Benefits: Enjoy remote work, flexible hours, generous leave, and competitive benefits.
- Other info: Work on meaningful projects that drive social and environmental change.
- Why this job: Make a real impact with your skills in a supportive, people-oriented culture.
- Qualifications: 5+ years in ML production, expertise in NLP/LLMs or similar fields.
The predicted salary is between 70000 - 90000 £ per year.
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 holiday 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.
Senior Data Scientist UK employer: Satalia (NPComplete)
Satalia is an exceptional employer that champions a people-oriented culture, prioritising wellbeing and fostering a transparent environment where every voice is valued. With fully remote working options, flexible hours, and a commitment to impactful projects, employees are empowered to thrive both personally and professionally. The company also offers generous benefits, including enhanced pension plans and ample leave, ensuring that team members can balance their work and life commitments effectively.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist UK
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and ML. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to data science. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Senior Data Scientist UK
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Data Scientist role. Highlight your hands-on experience with ML models and any relevant projects you've led, especially those involving LLMs or causal inference.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and how your background aligns with our mission at Satalia. Share specific examples of your work that demonstrate your expertise and problem-solving skills.
Showcase Your Communication Skills:Since clear communication is key, ensure your application materials are well-structured and easy to read. We want to see that you can write effectively for both technical and non-technical audiences.
Apply Through Our Website:We encourage you to apply directly through our website. This way, your application will be processed more efficiently, and you'll have access to all the latest updates about the role and our company.
How to prepare for a job interview at Satalia (NPComplete)
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, especially around NLP and LLMs. Be ready to discuss your past projects in detail, focusing on the challenges you faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific problems you've solved in production environments. Highlight your experience with data drift and model retraining, and be ready to explain your thought process when making build-vs-buy decisions.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You might need to write a design doc during the interview, so being able to communicate effectively with both technical and non-technical audiences is key.
✨Be Ready for Ambiguity
Since many of the problems at Satalia don’t have clear solutions, prepare to discuss how you handle uncertainty. Share examples of how you've navigated ambiguous situations in your previous roles and what strategies you used to find clarity.