Data Scientist

Data Scientist (Generative AI)

London, United Kingdom (Flexible hybrid working)

Permanent

ROLE SUMMARY

We are seeking a highly capable and innovative Data Scientist with specialized experience in Generative AI to join our Data Science Team. In this role, you will lead the development and deployment of enterprise-grade GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG).

The ideal candidate possesses a strong foundation in machine learning and NLP, paired with hands-on experience using modern GenAI frameworks and cloud environments.

KEY RESPONSIBILITIES

• Design &​ Build: Develop Generative AI solutions using Large Language Models (LLMs) across enterprise use cases such as customer service, document automation, summarization, and knowledge retrieval.
• Model Adaptation:

Fine-tune and adapt foundation models using domain-specific datasets.

• Pipeline Architecture: Implement RAG pipelines, embedding models, and vector databases (e.g., FAISS, Pinecone, ChromaDB).
• Cross-Functional Collaboration:

Partner with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs.

• Prompt Engineering: Develop custom prompts and prompt chains utilizing frameworks like LangChain, LlamaIndex, PromptFlow, or custom code.
• Optimization &​ Governance:

Evaluate model performance, mitigate bias, and optimize accuracy, latency, and operational cost.

• Innovation: Stay current with the latest advancements in LLMs, transformers, and GenAI system architecture.

Essential Qualifications

• 5+ years of professional experience in Data Science / ML, with 1+ year of hands-on delivery in LLM / GenAI projects.
• Strong Python Skills:

Expertise with libraries such as Transformers, LangChain, scikit-learn, PyTorch, or TensorFlow.

• LLM Expertise: Direct experience working with foundation models such as OpenAI (GPT-4), Claude, Mistral, LLaMA, or similar architectures.
• Semantic Search &​ Embeddings:

Deep understanding of vector search, embedding models (e.g., BERT, Sentence Transformers), and retrieval techniques.

• Deployment: Demonstrated ability to build scalable AI workflows and deploy them via APIs or web frameworks (e.g., FastAPI, Streamlit, Flask).
• Cloud &​ MLOps:

Familiarity with major cloud providers (AWS, GCP, Azure) and MLOps best practices.

• Communication: Exceptional ability to translate complex technical solutions into strategic business impact.

Desirable Skills

• Hands-on experience with prompt tuning, few-shot learning, or LoRA-based fine-tuning.
• Practical knowledge of data privacy, security, and governance considerations within GenAI systems.
• Familiarity with enterprise architecture, SDLC, or building solutions within highly regulated domains (finance, healthcare, insurance).
• Knowledge of Palantir tools is a strong bonus