Lead Data Scientist

An innovative, technology-driven consultancy organisation is seeking a Principal Data Scientist to lead the design and delivery of large-scale, high-impact AI solutions. This is a strategic leadership role at the forefront of enterprise AI transformation, combining deep technical expertise with commercial influence.

The successful candidate will take ownership of delivering production-grade AI and machine learning systems powered by advanced techniques in generative AI, agentic AI, and modern ML engineering. Operating at enterprise scale, they will shape AI strategy, champion cloud-native architectures, and drive the adoption of best-in-class AI development practices across the organisation.

The Role

As a senior technical leader, the Principal Data Scientist will:

• Lead the successful delivery of complex, enterprise AI/ML programmes.
• Define architectural principles and strategic direction for AI and data science.
• Engage C-level and senior stakeholders, translating advanced AI concepts into tangible business value.
• Embed modern AI engineering standards, scalable MLOps practices, and responsible AI governance.
• Drive innovation across supervised and unsupervised learning, time series modelling, reinforcement learning, large language models (LLMs), and agentic AI systems.
• Foster a culture of innovation, continuous learning, and engineering excellence.

Beyond technical leadership, this role plays a critical part in strengthening customer partnerships, shaping commercial AI offerings, and influencing account strategy to maximise measurable ROI from AI investments.

Leadership & Impact

The Principal Data Scientist will build, mentor, and inspire a high-performing community of data scientists, AI engineers, and technical managers. They will ensure robust delivery standards while promoting ethical, interpretable, and secure AI solutions.

Working closely with sales and account leadership, they will help shape AI propositions, support business development, and ensure AI initiatives deliver sustainable commercial success.

Essential Experience

• Proven accountability for delivering complex, production-grade AI/ML solutions at scale.
• Demonstrated technical leadership across enterprise AI initiatives.
• Deep expertise in advanced AI/ML methodologies, including:
• Time series forecasting
• Supervised and unsupervised learning
• Reinforcement learning
• Large Language Models (LLMs)
• Agentic AI architectures
• Experience with modern AI engineering approaches such as:
• Prompt engineering
• Retrieval-Augmented Generation (RAG)
• Orchestrating agent-based AI systems
• Strong data engineering capability, including handling large-scale, unstructured, and multimodal datasets.
• Comprehensive understanding of responsible AI, model interpretability, governance, and ethical frameworks.
• Ability to influence and negotiate at C-level, clearly articulating the commercial value of AI.
• Experience shaping AI-led account strategies and commercial offerings.
• Demonstrated success building and leading high-performing AI and Data Science teams.
• Strong commercial acumen with a track record of driving AI product and solution success.

Desirable Experience

• Hands-on expertise with modern deep learning frameworks such as PyTorch and TensorFlow.
• Experience fine-tuning or distilling large language models (e.g., GPT, Llama, Claude, Gemini).
• Proficiency with advanced ML libraries including scikit-learn and XGBoost.
• Experience with vector databases, semantic search, knowledge graphs, and AI data storage architectures.
• Contributions to open-source AI projects, research publications, or industry events.
• Familiarity with AI security, privacy, and compliance standards such as ISO 42001.