Data Scientist Manager
On-siteLondon, England, United Kingdom or Belfast, Northern Ireland, United Kingdom
Job Summary
Lead delivery of advanced AI solutions leveraging state-of-the-art machine learning, generative, and agentic AI technologies while driving adoption of modern AI development and scalable cloud-native architectures. Engage with senior stakeholders to agree architectural principles, strategic direction, and system architecture, fostering a culture of innovation and engineering excellence. Manage and coach a multi-disciplinary team, establishing standards, policies, and enduring customer relationships with a focus on commercial acumen. Solve challenging technical problems through technical leadership, requiring a 2.1 degree in a quantitative field and proven experience in leading teams to deliver high-quality AI/ML solutions.
Required Qualifications
- A minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field
- Proven experience of leading multi-disciplinary teams to deliver high quality AI/ML solutions
- Demonstrable experience of technical leadership for AI delivery including architecture, product design principles and engineering excellence
- Have a deep understanding and developing of AI/ML models, including time series, supervised/unsupervised learning, reinforcement learning and LLMs
- Experience with the latest AI engineering approaches such as prompt engineering, retrieval-augmented generation (RAG) and agentic AI
- Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc)
- Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data
- Understanding of responsible AI principles, model interpretability and ethical considerations
- Strong interpersonal skills with the ability to lead client projects, manage C-level stakeholders and establish requirements/architecture concepts
- Experience in managing, coaching and developing junior members of a team and wider community
Desired Qualifications
- Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow)
- Fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini)
- Machine learning libraries (e.g. scikit-learn, XGBoost)
- Experience with data storage for AI, vector databases, semantic search and knowledge graphs
- Actively contributes to open-source AI projects, research publications and industry events/websites
- Familiarity with AI security, privacy, and compliance standards e.g. ISO42001
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