Data Scientist at a banking company in São Paulo. Focused on process optimization and data analysis to enhance decision making and customer behavior predictions.
About the role
- 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
- Learning opportunities around D&I
Job title
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