Senior Data Scientist, Lloyds

• Graduate-level education (Master’s or PhD) in Computer science, Statistics, Mathematics, Physics or a similar field
• Substantial background in data science or machine learning
• Strong expertise in anomaly detection techniques (statistical, ML-based, and deep learning approaches)
• Hands-on experience with large language models (LLMs) and retrieval-augmented generation (RAG)
• Some experience building or working with agentic or autonomous AI systems
• Proficiency in Python and common data science/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
• Solid background in working with Google Cloud Platform (GCP), including services such as BigQuery, Vertex AI, Dataflow, and Cloud Storage
• Solid understanding of data pipelines, distributed systems, and MLOps practices in a cloud-native environment

Desirable

• We're looking for a Senior Data Scientist to join the Security Data & AI (SD&AI) Lab within the Chief Scientific Office (CSO)
• This role focuses on designing and delivering advanced AI/ML solutions to address complex security challenges using Google Cloud Platform (GCP)
• This role will lead the development of scalable models and systems across areas such as anomaly detection, agentic AI, and large language models (LLMs) to enhance contextual intelligence in security workflows
• You'll work on end-to-end data science solutions: from experimentation to production, leveraging GCP services
• The role requires strong technical expertise, leadership, and collaboration with cross-functional teams to translate business needs into impactful, production-ready AI solutions
• This is a high-impact position driving innovation in intelligent threat detection, response, and overall security capabilities
• Lead the build, development, and deployment of advanced machine learning and AI models for security use cases
• Develop and improve anomaly detection systems across structured and unstructured datasets
• Architect and implement agentic AI systems capable of autonomous reasoning, decision-making, and task execution in security contexts
• Leverage LLMs to build contextual intelligence layers that enrich detection, triage, and response workflows
• Build and operationalise data pipelines using GCP services (e.g., BigQuery, Dataflow, Pub/Sub) for large-scale data processing
• Deploy and manage ML models using GCP tools, ensuring scalability, monitoring, and lifecycle management
• Collaborate with cross-functional teams (data engineering, security analysts, product, and analytics) to translate business problems into data-driven solutions
• Drive experimentation, prototyping, and evaluation of brand-new AI techniques
• Ensure models are production-ready, scalable, explainable, and aligned with security and governance standards
• Mentor junior data scientists and contribute to technical leadership within the lab
• Stay up to date with emerging trends in AI, cloud technologies, and cybersecurity

• End Date: Monday 04 May 2026