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Lead Data Scientist (Classical ML, LLMs & AI Agents)
Talan
London, GBR
Full-time
Senior · 5+ years experience
Hybrid
Discovered 2 weeks ago
PythonAzure MLAzure OpenAIDatabricksFabricUdemy for Business
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PythonAzure MLAzure OpenAI
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PythonAzure MLAzure OpenAIDatabricksFabricUdemy for Business
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Required skills & experience
- Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.
- Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.
- Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.
- Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.
- Ensure best practice across the AI lifecycle — experimentation, evaluation, testing, deployment, and monitoring.
- Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.
- Support pre-sales and client discussions with credible technical input and realistic estimation.
- Champion reproducibility, model governance, and responsible practice in everyday delivery.
To qualify for this role, you must have
- Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.
- Strong foundations in machine learning and statistics, with demonstrable production experience.
- Practical experience with LLMs and generative AI — prompting, RAG, fine-tuning, and evaluation.
- Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.
- Proficiency in Python and the modern data / ML stack; sound data engineering instincts.
- Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.
Ideally, you’ll also have, but not essential
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).
Experience supporting business development or pre-sales.
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