Data Science and AI Graduate Scheme

Lloyds Banking Group is a financial services organization focused on using data, analytics and AI to improve decision-making and customer outcomes. The Data Science & AI Graduate will complete two rotations involving model training, algorithm development, scalable solution deployment, advanced analytics, machine learning, generative AI and responsible AI practices.

Responsibilities:

• 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