Data Scientist

Experis; Greater London; Hybrid; GBP 81,000 - 99,000; Full time

Benefits offered by this job

Life assurance

Employee share purchase programme

Flexible hybrid working

Job summary

Experis is seeking a Data Scientist with Generative AI experience to join its Data & AI practice in the UK. You will design, build and deploy GenAI solutions across industries, working with multidisciplinary teams to deliver production-ready AI applications.

You will develop LLM-powered apps for document automation, knowledge retrieval, summarisation and customer support, plus RAG solutions and model fine-tuning on domain data.

Qualifications

• 5+ years of experience in Data Science, ML, or AI.
• Commercial experience delivering Generative AI or LLM-based solutions.

Responsibilities

• Design, build and deploy Generative AI solutions across industries.
• Develop LLM-powered apps for document automation, knowledge retrieval, summarisation and customer support.
• Design and implement Retrieval-Augmented Generation (RAG) solutions.
• Fine-tune foundation models using domain-specific data.
• Build embedding pipelines with FAISS, Pinecone or ChromaDB.
• Create prompt engineering frameworks and chains using LangChain or similar tools.
• Collaborate with Data Eng, MLOps and Product teams to deploy scalable AI solutions.
• Evaluate model performance and optimize cost, accuracy, latency and reliability.

Skills

5+ years experience

Commercial GenAI/LLM experience

Tools

FAISS

Pinecone

ChromaDB

FastAPI/Flask/Streamlit

AWS/Azure/GCP

Job description

A leading global Data & AI consultancy is looking for a Data Scientist with Generative AI experience to join its growing AI practice. This is an exciting opportunity to work on cutting-edge GenAI initiatives, helping enterprise clients unlock value through Large Language Models (LLMs), automation, and intelligent decision-making.

About the Role

You’ll be responsible for designing, building, and deploying Generative AI solutions across a range of industries, collaborating with multidisciplinary teams to deliver production-ready AI applications.

Responsibilities

• Developing LLM-powered applications for business use cases such as document automation, knowledge retrieval, summarisation, and customer support.
• Designing and implementing Retrieval-Augmented Generation (RAG) solutions.
• Fine-tuning and adapting foundation models using domain-specific datasets.
• Building embedding pipelines and working with vector databases including FAISS, Pinecone, or ChromaDB.
• Creating prompt engineering frameworks and prompt chains using LangChain, LlamaIndex, PromptFlow, or similar tools.
• Collaborating with Data Engineering, MLOps, and Product teams to deploy scalable AI solutions.
• Evaluating model performance and optimising cost, accuracy, latency, and reliability.
• Staying current with advancements in GenAI, transformers, and LLM architectures.

Qualifications

• 5+ years' experience in Data Science, Machine Learning, or AI.
• Commercial experience delivering Generative AI or LLM-based solutions.

Required Skills

• Experience with technologies such as:
• RAG, Vector Search, Embeddings
• Experience deploying AI applications using FastAPI, Flask, Streamlit, or similar frameworks.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Excellent communication and stakeholder management skills.

Preferred Skills

• Prompt tuning, LoRA fine-tuning, or few-shot learning experience.
• Understanding of AI governance, privacy, and security considerations.
• Experience within regulated sectors such as Financial Services, Insurance, or Healthcare.
• Exposure to Palantir Foundry.

Pay range and compensation package

• Up to £90,000 base salary
• 10% annual bonus
• Life assurance
• Employee share purchase programme
• Ongoing learning and development opportunities
• Flexible hybrid working

Equal Opportunity Statement

Applicants must have the right to work in the UK and be able to start within a maximum 1-month notice period. To learn more, please get in touch for a confidential discussion.