Head of Data Science

A leading healthcare consulting firm is seeking a Principal Consultant in Advanced Analytics to provide statistical expertise and methodological leadership across projects. The role includes directing project teams, ensuring quality standards, and driving new business..., A leading technology firm in the UK is seeking a Head of Data Science to lead the development and implementation of advanced AI solutions. The ideal candidate will have significant leadership experience in data science, a track record of managing diverse teams, and..., A global business is seeking a Head of Data Science to lead a high-performing Data Science team. This role offers the freedom to shape data solutions that impact millions daily, engaging hands-on with model development and collaboration with engineering teams to deliver..., Purpose Of This Role The Principal Consultant, Advanced Analytics: Data Science and AI contributes statistical capabilities and methodological leadership at all stages of projects, from planning to completion. The role includes working with junior team members in...

We are looking for an AI Engineer to join our Data Science team, building AI-powered solutions for clinical data processing and analysis within a major pharmaceutical organization. You will design, develop and deploy generative AI systems that automate clinical reporting workflows, extract intelligence from documents, and accelerate data-driven decision making. This is a hands-on engineering role - you'll be writing production code, not just building prototypes. ResponsibilitiesGenerative AI & Automation: Develop LLM-powered automation tools for clinical reporting and document generation workflows Build AI-driven code generation pipelines and quality assessment frameworks Design and implement human-in-the-loop review workflows with feedback loops to continuously improve output quality Research & Evaluation: Research and evaluate emerging AI methods, frameworks, and techniques for specific tasks - e.g. comparing fine-tuning vs zero-shot approaches, assessing new document extraction tools, or trialling new agentic frameworks Prototype and benchmark new approaches before recommending adoption Stay current with a rapidly evolving field and bring new ideas to the team Agentic AI & Orchestration: Design and build multi-agent systems for data workflows - agents that retrieve, generate, validate, and iterate autonomously Implement agent orchestration using frameworks such as Google ADK, LangGraph, or LangChain Deploy and manage agents on Google Vertex AI Design and build RAG pipelines grounded in source documents Process, extract and transform data from unstructured and semi-structured sources Code Quality & Engineering Practices: Write clean, well-tested, maintainable Python code following SOLID principles and recognised design patterns Apply single responsibility, dependency inversion, and interface segregation in real codebases - not just theory Write meaningful tests, and maintain high standards across the team Refactor and improve existing code as part of normal development workflow AI-Assisted Development: Use AI coding tools (e.g. Gemini CLI, GitHub Copilot) as a core part of your development workflow Critically review and validate AI-generated code - understanding what it produces, why, and when it's wrong Write effective prompts to direct AI tools toward correct, secure, well-structured output Know when to use AI and when to write code manually - judgement over speed Platform & Infrastructure: Integrate and orchestrate LLM providers available through Google Vertex AI (Gemini, etc.) Build internal tools and applications using Streamlit and FastAPI Containerize and deploy services using Docker Required Skills & ExperienceMSc in Data Science, Computer Science, Bioinformatics, or related field (or equivalent practical experience) Hands-on experience building RAG systems or LLM-powered applications (using LangChain, LlamaIndex, or similar frameworks) Experience integrating LLM APIs (Google Gemini, OpenAI, or similar) - we work primarily through Google Vertex AI Working knowledge of vector databases (ChromaDB, Weaviate, Qdrant, Pinecone, or similar) Cloud platform experience (GCP preferred, especially Vertex AI) Docker and containerized deployments Strong software engineering fundamentals - SOLID principles, clean code practices, design patterns, testing, version control (Git), code review Comfortable using AI-assisted development tools (e.g. Gemini CLI, GitHub Copilot) - and critically evaluating what they produce Strongly PreferredExperience with agentic AI patterns - multi-agent orchestration, tool use, autonomous workflows (LangGraph, Google ADK, or similar) Document processing experience - extracting and parsing data from PDFs and Word/DOCX files programmatically Understanding of LLM evaluation principles and output quality assessment (BLEU, ROUGE etc, code execution metrics, or similar) Data science fundamentals - Pandas, NumPy, scikit-learn, statistical analysis, data visualization Prompt engineering and optimisation techniques Nice to HaveDomain KnowledgeClinical trials or pharmaceutical industry experience Familiarity with clinical data standards Awareness of regulatory and data privacy requirements in life sciences Infrastructure & DevOpsTerraform or infrastructure-as-code experience Knowledge GraphsNetworkX for graph analytics Graph-based RAG or knowledge extraction AI/MLExperience with LLM-driven code generation LLM fine-tuning experience (e.g. LoRA, PEFT, RLHF, Vertex AI model tuning, or similar approaches) NLP and text processing (HuggingFace Transformers, Sentence-Transformers) PyTorch or TensorFlow (for custom model work if needed) Google ADK (Agent Development Kit) or Vertex AI Agent Builder Model Context Protocol (MCP) for tool integration and interoperability OtherFrontend experience (React, TypeScript) FastAPI or Flask REST API development PostgreSQL or similar relational databases What You'll Work WithLanguages:Python (primary), SQL, some TypeScript/R Document Processing:PyMuPDF, python-docx, pdfplumber, OCR tools Data:Pandas, NumPy, SciPy, scikit-learn, Plotly Infrastructure:Docker, Google Cloud Platform (Vertex AI, GCS), Terraform, GitHub Actions Applications:Streamlit, FastAPI, Flask Tools:Python packaging, testing frameworks, linting, Git About YouYou care about code quality - not just making things work, but making them maintainable You're comfortable working across the full stack of an AI application, from data ingestion to user-facing tools You can context-switch between multiple projects and work autonomously You're curious about the clinical/pharmaceutical domain and motivated to learn it You see AI-assisted development as a force multiplier, not a replacement for engineering judgment You're a self-directed learner who researches new methods and tools, evaluates them critically, and knows when to adopt vs when to stick with what works#J-18808-Ljbffr Similar jobs

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A leading technology firm in the UK is hiring an AI Engineer to build AI-powered solutions for clinical data processing. You will design and implement generative AI systems to automate reporting workflows, work hands-on with production code, and research new AI methods....