Data Science & AI Lead

Closing date for applications: 19/07/2026 Location London, United Kingdom Job typePermanent | Contract typeFull Time Remote / On-site Hybrid You’ll spend some of your time at home, working with your team digitally. You’ll also regularly work at your office or hub to collaborate with your colleagues. Senior Manager This is a general indication and doesn’t always reflect day-to-day responsibilities. Check the job description for full details. R-00281978 Job description ------------------- This role is based in the United Kingdom and as such all normal working days must be carried out in the United Kingdom. Join us as a Data Science \& AI Lead * In this key role, you’ll lead Data Science and AI capabilities for the Economic Crime Hub, designing, building, and scaling production-grade models, AI systems, and automated decisioning solutions * You’ll own the end-to-end lifecycle of models and AI agents, ensuring decisions are executed safely, consistently, and effectively at scale * Make an impact by building a high-performing Data Science and Machine Learning (ML) Engineering capability that drives innovation and business outcomes through AI and advanced analytics What you'll do ------------------ As a Data Science \& AI Lead, you'll own the end-to-end Data Science and AI agenda, delivering scalable models, AI systems, and agentic workflows embedded within decision-making across the Hub. You’ll oversee the design, build, and deployment of models and AI solutions into production environments, ensuring they deliver reliable, high-performing outcomes that support business objectives at scale. You’ll also establish and enforce standards for model development, Machine Learning Operations (MLOps), monitoring, and lifecycle management, while partnering closely with Analytics, Product, and Technology teams to translate decision strategies and decision intent into automated, production-grade solutions, ensuring technical feasibility, scalability, and integrity. Moreover, you’ll build and lead a multi-disciplinary Data Science capability, encompassing Data Scientists, ML Engineers, and MLOps specialists, ensuring strong technical depth, continuous development, and clear progression across the function. In addition, you’ll be: * Acting as the single-threaded owner for the automation of decision-making, translating analytical logic and decision strategies into production-grade models and AI systems across the full lifecycle * Overseeing model performance, including accuracy, stability, drift, reliability, and the real-world effectiveness of decision-making in production environments * Embedding controls, validation, monitoring, and safeguards into models and AI systems by design * Advancing AI and ML capabilities, including agentic AI, Large Language Model (LLM) use cases, MLOps, and automation frameworks, while increasing automation without adding risk or control debt * Designing scalable architectures, standardised pipelines, and reusable model components to enable efficient and repeatable delivery * Building a high-performing Data Science, ML Engineering, and MLOps function, driving technical excellence, innovation, and career development * Ensuring models are explainable, traceable, auditable, and compliant with governance frameworks, while partnering with Model Risk on technical implementation and model behaviour The skills you'll need -------------------------- We're looking for someone with extensive experience leading engineering-grade Data Science and AI capabilities, delivering scalable, automated decisioning systems. You must have a proven track record of designing and deploying AI-driven solutions, leveraging advanced modelling techniques and emerging approaches such as LLMs and agentic workflows. Moreover, you'll need to bring technical expertise to lead the delivery of production-grade AI solutions and guide their adoption within a complex, regulated environment. You should also have the ability to provide technical leadership, foster high-performing teams, and drive innovation while maintaining strong governance and risk management practices. Experience working within financial crime or fraud environments would be preferred In addition, you’ll need to demonstrate: * Deep expertise in model development and lifecycle management, including building, deploying, monitoring, retraining, and retiring models in production environments * Strong knowledge of MLOps, model monitoring, and production systems, ensuring the reliability, performance, and operational effectiveness of models and automated decisioning * Experience working within regulated environments, with a strong understanding of model governance, explainability, auditability, and data risk management * Success in building and scaling high-performing teams across Data Science, ML Engineering, and MLOps functions Your benefits breakdown --------------------------- Here’s a quick look at what your pay package and annual leave could look like if you get accepted for the role. We have a wide range of benefits to support you in your working life and beyond. Tap each segment for details. Your pay package 100% Base pay This is your base pay package that you take home every month. +10% Pension funding This is monthly funding paid towards your pension. up to +10% Benefit funding This is monthly funding paid towards a range of benefits you can choose from. Your leave allowance 30 days Annual leave You’ll also have the opportunity to purchase up to 5 additional days off. 3 days Volunteering Take time off to support the causes you’re passionate about. 3 days Training Take time to build the skills you need to grow your career. Total rewards package Welcome to our Bishopsgate hub ---------------------------------- Based only a few minutes’ walk from Liverpool Street Station, the central location of this office makes working there incredibly convenient. Everything you need is close by, so you can run errands, go to the gym, and socialise with friends and colleagues before and after work. Bishopsgate recently underwent a multi-year refurbishment programme to improve spaces and facilities as well as become more sustainable.