Data Science and AI Industrial Placement

End Date Saturday 07 November 2026 Salary Range £29,000

Before you start your application, please note alternative formats are available on request.

We will get back to you as soon as we can but during busy times, it might take up to 5 working days (Don't worry, this won't affect your progress in the application process)

Job Description Summary Prior to submitting your application, please visit our early careers website to find out more about the schemes we offer and the recruitment journey:  Our industrial placements may close early if we receive a high number of applications, so it's best to apply as soon as you can.

Job Description Your AI era starts now At Lloyds Banking Group, data isn't just something we store in the cloud. It's the juice that keeps ideas flowing, decisions sharper, and progress unstoppable. Our Chief Data & Analytics Office has one mission: weave data, analytics and AI into every decision we make. The goal? Simple. Every choice, everywhere, driven by data. As a Data Science & AI Graduate, you won't be on the sidelines watching the algorithms run the show.

You'll be training models, crafting algorithms, deploying scalable solutions, and showing exactly what AI can do in the real world. Whether you're optimising performance, unlocking insight or making predictions, everything you do will be rooted in data literacy, ethics and genuine business impact. One year. Real impact Throughout this placement, you'll do everything a Data & AI Scientist does. And while you build out your technical expertise within a specific team from the outset, your impact will be felt throughout the business.

• Cloud-native AI engineering and large-scale data platforms, leveraging Google Cloud technologies and modern coding practices to design, build and deploy intelligent solutions, helping the Bank innovate rapidly and deliver value at scale.
• Advanced analytics, statistical learning and decision intelligence, applying quantitative techniques to uncover patterns, generate insights and optimise outcomes, enabling more informed decisions for both the business and its customers.
• Machine Learning, predictive modelling and applied AI, developing, evaluating and ope rationalising models using state-of-the-art libraries and frameworks such as scikit-learn, Tensor Flow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation.
• Generative AI, Large Language Models and autonomous agent systems, building next-generation AI applications using foundation models, retrieval-augmented generation (RAG) architectures and agent frameworks such as Google ADK and Lang Chain, helping transform how the Bank serves customers and empowers colleagues.
• Data engineering, MLOps and intelligent automation, creating resilient data pipelines, scalable deployment architectures and automated machine learning workflows using contemporary engineering and CI/CD practices, enabling AI solutions to operate reliably across the enterprise.
• AI assurance, evaluation science and model governance, designing rigorous testing, monitoring and validation frameworks for machine learning models and agentic systems, ensuring AI solutions remain robust, trustworthy and aligned to the Bank's strategic objectives.
• Responsible AI, explainability and algorithmic governance, applying principles of fairness, transparency, interpretability and risk management throughout the AI lifecycle, helping maintain customer trust while delivering innovative AI capabilities.

• Python & SQL
• Cloud platforms like GCP
• Data Analysis
• Machine learning techniques, both theory and application
• Generative and Agentic AI
• AI Solution design…