Data Scientist specialising in NLP at M+C Saatchi World Services. Designing and implementing language systems to enhance product understanding and generation.
Responsibilities
Design and build LLM‑powered applications using third‑party APIs (OpenAI, Anthropic, etc.)
Develop RAG (retrieval‑augmented generation) systems including document ingestion, chunking strategies, and vector search infrastructure
Implement advanced prompt‑engineering patterns, evaluation frameworks, and output‑reliability mechanisms
Build NLP pipelines for text classification, entity extraction, semantic search, summarisation, and document understanding
Develop agentic workflows and tool‑use systems for complex multi‑step tasks
Optimise for cost, latency, reliability, and model selection across LLM providers and configurations
Collaborate with product and engineering teams to translate business requirements into robust technical solutions
Build monitoring, observability, and evaluation systems for LLM applications in production
Requirements
Solid experience in applied NLP or machine learning roles
Strong proficiency in Python and experience building production systems
Hands‑on experience with LLM APIs (OpenAI, Anthropic, or similar)
Experience building RAG systems including loaders, text splitting, embedding models, and vector stores
Solid understanding of NLP fundamentals: embeddings, semantic similarity, text classification, and evaluation
Experience with prompt engineering and structured output parsing
Strong software engineering fundamentals: version control, testing, code review, documentation
Experience with cloud infrastructure (AWS preferred)
Desirable: Experience with LLM orchestration frameworks (LangChain, LlamaIndex, etc.)
Background working with vector databases (Pinecone, Weaviate, pgvector, Chroma)
Experience building agentic LLM workflows (tool calling, function calling, multi‑step reasoning)
Familiarity with LLM evaluation and observability tools (LangSmith, Weights & Biases, etc.)
Experience fine‑tuning API‑based models or working with embedding models
Understanding of cost‑optimisation strategies across providers and model tiers.
Benefits
27 days holiday per year
Pension contributions
Private healthcare
Discounted dental insurance
Enhanced maternity/parental leave
Cultural stimulation allowance - £250 per person per year
Half days off before bank holidays
Emergency care days for dependants
Up to 5 days volunteering leave per year to work for a registered charity
Up to 10 days special emergency leave per year
Season Ticket loan
Payroll Giving Scheme
Thursday drinks to unwind and socialize
An annual Summer and Christmas party
Commitment to Diversity and Inclusion including inclusive bank holidays
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