End Date

Sunday 29 November 2026

Salary Range

£48,500

Before you start your application, please note alternative formats are available on request. Please contact us by emailing lloydsbankinggrouptalent@peoplescout.co.uk or calling on 0345 330 4576. If emailing, please tell us how you would like us to respond - we can email back or call you to discuss any requirements or concerns you might have. 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: www.lloydsbankinggrouptalent.com.

Our graduate schemes may close early if we receive a high number of applications, so it’s best to apply as soon as you can.

If you have any questions, please do contact the team at lloydsbankinggrouptalent@peoplescout.co.uk

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.

Two years. Two game-changing rotations

This two-year programme blends office and home working. Across two year-long placements, you’ll see how we use data and AI to crack big-ticket challenges. From detecting fraud and managing credit risk to decoding customer behaviour and building smarter banking tools.

You could become:

• A Data & AI Scientist uncovering insights, making predictions and solving complex problems with machine learning techniques. Always with an ethical and accurate lens.
• A Machine Learning & AI Engineer designing and deploying robust ML systems that bring data science to life through automation, CI/CD, and modern cloud engineering practices.

Wherever you land, you’ll be working with some of the biggest datasets in the UK — using everything from Spark and statistical methods to domain knowledge and emerging GenAI applications.

The work you could be doing

• 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.