Data Science & AI Industrial Placement - Leeds

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.

You’ll be placed in a team working on:

• 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 operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, 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 LangChain, 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.