Data Scientist


Company 

McGregor Boyall

Location 

London

Employment Hours 

Full Time

Employment Type 

Permanent

Salary 

£65,000 Per Annum

Job Requirements/Description
Job Title: Data Scientist (LLMs & ML) - UK Remote

A fast-growing healthcare organization is seeking a Data Scientist with strong experience in machine learning, deep learning, and Large Language Models (LLMs) to help drive innovation and automation in clinical services. This is a full-time, remote UK-based role.

Unfortunately we can't consider candidates that require sponsorship

Key Responsibilities:
  • Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems.

  • Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost.

  • Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing.

  • Manage ML lifecycle with tools such as Databricks, MLflow, and cloud-native platforms (Azure preferred).

  • Collaborate with engineering teams to ensure scalable, secure ML infrastructure aligned with compliance standards (e.g., ISO27001).

  • Ensure data governance, particularly around sensitive healthcare data.

  • Share best practices and stay current with developments in AI, ML, and LLMs.

Requirements:
  • Proven experience with LLM frameworks and transformer-based architectures.

  • Strong Python skills and familiarity with key ML/DL libraries.

  • Experience with Azure (or similar cloud platforms), containerization (Docker/Kubernetes a plus), and MLOps tools.

  • Understanding of healthcare data privacy, compliance (e.g., ISO standards), and secure data handling.

  • Strong communication skills and ability to work cross-functionally in a collaborative environment

McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.

Company 

McGregor Boyall

Location 

London

Employment Hours 

Full Time

Employment Type 

Permanent

Salary 

£65,000 Per Annum

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