Data Scientist x 2

Tank Recruitment

Greater London

Hybrid

GBP 80,000 - 120,000

Full time

2 days ago
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Benefits offered by this job

Competitive salary plus bonus
Private healthcare, life assurance, +p
Flexible hybrid working model

Job summary

Tank Recruitment is seeking a Data Scientist (Generative AI) in London with hybrid working options. The role focuses on leading GenAI projects, developing LLM-based applications, and deploying AI workflows at scale. Strong ML/NLP background and hands-on GenAI tooling are required.

You will collaborate with data engineers, MLOps, and product teams to deliver end-to-end AI applications and APIs, while ensuring model performance, bias mitigation, and cost efficiency.

Qualifications

  • Strong foundation in machine learning and NLP.
  • Hands-on experience with GenAI projects.
  • Proficiency in Python.
  • Experience with LLMs/GenAI applications.

Responsibilities

  • Lead development and deployment of GenAI solutions for enterprise use cases.
  • Fine-tune or adapt foundation models using domain data.
  • Implement retrieval-augmented generation and embedding models.
  • Collaborate with data engineers and product teams to build end-to-end AI apps and APIs.
  • Develop prompts and prompt chains for orchestration frameworks.
  • Evaluate model performance and optimize for accuracy, latency and cost.
  • Stay current with trends in LLMs, transformers, and GenAI architecture.

Job description

Role: Data Scientist (Generative AI)
Location: London, United Kingdom (flexible hybrid)
Type: Permanent - Immediate start.

My client, a well established global data and AI consultancy serving major organisations across sectors including insurance, healthcare, banking and retail, is looking for a highly capable and innovative Data Scientist with strong Generative AI experience to join their Data Science team.

The Role:

You’ll lead the development and deployment of GenAI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases. My client is after someone with a strong foundation in machine learning and NLP, and hands‑on experience with modern GenAI tools such as OpenAI, LangChain, Hugging Face, or comparable frameworks.

Key Responsibilities:
  • Design and build GenAI solutions using LLMs for business problems spanning customer service, document automation, summarisation, and knowledge retrieval
  • Fine‑tune or adapt foundation models using domain‑specific data
  • Implement RAG pipelines, embedding models, and vector databases (e.g., FAISS, Pinecone, ChromaDB)
  • Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs
  • Develop custom prompts and prompt chains using common orchestration frameworks
  • Evaluate model performance, mitigate bias, and optimise for accuracy, latency, and cost
  • Stay current with the latest trends in LLMs, transformers, and GenAI architecture
  • Solid experience in Data Science / ML, including recent hands‑on work with LLMs/GenAI projects
  • Strong Python skills, particularly with Transformers, LangChain, scikit‑learn, PyTorch, or TensorFlow
  • Experience with GPT-4, Claude, Mistral, LLaMA, or similar models
  • Knowledge of vector search, embedding models, and semantic search techniques
  • Ability to build and deploy scalable AI workflows via APIs or web apps (e.g., FastAPI, Streamlit, Flask)
  • Familiarity with major cloud platforms and MLOps best practices
  • Strong communication skills, with the ability to translate technical solutions into business impact
  • Experience with prompt tuning, few‑shot learning, or LoRA‑based fine‑tuning
  • Understanding of data privacy and security considerations in GenAI applications
  • Familiarity with enterprise architecture, SDLC, or GenAI use cases in regulated industries
  • Experience with enterprise data platform tools is a plus
What's on Offer:
  • Competitive salary plus bonus
  • Private healthcare, life assurance, income protection, and pension scheme
  • Additional financial wellbeing benefitsStrong investment in professional development and training
  • Flexible hybrid working model
  • A genuinely inclusive, equal‑opportunity employer
Please note:

candidates must already hold the right to work in the United Kingdom.

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