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Senior Data Scientist - Generative AI

Summary

Build and productionise generative AI solutions like LLM apps and RAG systems to deliver measurable business value.

Senior Data Scientist – Generative AI

Perm Role

Location – London – 3 Days in Office

Salary – Upto £73K

Senior Data Scientist – Generative AI

  • Lead the development of next-generation AI solutions by designing, building and productionising advanced data science, machine learning and Generative AI solutions that deliver measurable business value across the organisation.
  • Drive Generative AI innovation through hands-on development of LLM applications, Retrieval-Augmented Generation (RAG), semantic search, embeddings, vector databases, prompt engineering, summarisation, classification, question answering and intelligent content generation.
  • Apply advanced data science and machine learning across predictive modelling, forecasting, classification, optimisation, anomaly detection, NLP and statistical modelling, selecting the right techniques to solve complex business challenges.
  • Own the full data science lifecycle, from opportunity discovery and experimentation through model development, evaluation, deployment, monitoring and continuous improvement, applying robust approaches to accuracy, relevance, reliability, bias, safety, hallucination risk, cost and performance.
  • Work with modern data and AI platforms including Databricks, Spark, Microsoft Fabric, Azure AI Services and Azure Machine Learning to develop scalable solutions and leverage lakehouse architectures for large-scale data preparation and experimentation.
  • Champion MLOps and engineering excellence through Python and SQL development, Git, automated testing, CI/CD, model registries, experiment tracking, monitoring, reusable components and production-ready development practices.
  • Provide technical leadership and collaboration by shaping data science approaches, leading design reviews, mentoring colleagues and partnering with Data Engineers, Analytics Engineers, Product Owners and business stakeholders to turn ambiguous problems into practical AI solutions.
  • Promote responsible and innovative AI adoption by evaluating emerging technologies, using AI-assisted development tools responsibly and applying strong judgement around data privacy, security, governance, ethical AI and model risk. Relevant Azure, Databricks, Generative AI, NLP or MLOps certifications are advantageous.


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