Data Scientist (AI) - 12 month contract

• Contract Type Day Rate Contractor
• Closing Date 21 August, 2026
• Job Category Tech, Data and Digital
• Business Unit Systems and Infrastructure (UKT)
• Location London OR Manchester, United Kingdom
• Posted on 22 July, 2026

The opportunity 

As a Data Scientist, you will work hands-on with data, models, and advanced analytics across the bank. You will develop, deploy, and continuously improve data science and machine learning solutions that support strategic and operational decision-making. You'll explore analytical approaches to complex business challenges, identify opportunities for value creation, and deliver data-driven insights that drive business outcomes.

Working across the full data science lifecycle, from problem definition and exploration through to deployment, monitoring, and evaluation, you'll collaborate closely with stakeholders across the organisation to understand business needs and translate them into effective analytical solutions. You will also play a key role in communicating insights clearly and effectively, ensuring decisions are grounded in robust analysis and evidence.

In this role, you'll have the freedom to investigate new analytical questions, the support of experienced colleagues, and opportunities to experiment with emerging tools, techniques, and methodologies in a collaborative and innovative environment.

Key responsibilities

• Developing, testing, deploying, and maintaining machine learning and statistical models in production environments. 
• Building scalable data science solutions using Python and SQL. 
• Applying software engineering best practices, including version control (Git), code reviews, testing, and documentation. 
• Using MLOps practices to support model deployment, monitoring, governance, and continuous improvement. 
• Working with large and complex datasets  
• Evaluating emerging technologies and analytical techniques to identify opportunities for innovation and business value. 
• Ensuring models and analytical solutions meet regulatory, governance, and risk management standards within a financial services environment. 
• Contribute to backlog refinement and sprint planning, stand-ups and retrospectives 
• Reinforce Agile ways of working, using pair programming, DORA insights and best practices to help to foster an environment of continuous improvement within the team  

What we’re looking for

Research (by Harvard University) shows that women are particularly likely to second guess themselves and not apply - so if you are worried you don't meet all the criteria, get in touch anyhow and let us do the worrying…

• Strong practical knowledge of statistics, mathematics, and machine learning techniques, with experience developing, validating, deploying, and monitoring predictive and analytical models in production environments.
• Advanced Python and SQL skills, with experience using tools such as Jupyter/JupyterHub to conduct data exploration, develop machine learning solutions, and support production workflows.
• Hands-on experience applying machine learning techniques using frameworks such as XGBoost, PyTorch, or similar technologies to solve complex business problems and deliver measurable value. 
• Experience translating business requirements into actionable analytical solutions, working closely with stakeholders to identify opportunities, define approaches, and deliver data-driven outcomes.
• Strong communication skills, with the ability to explain complex technical concepts and analytical findings to both technical and non-technical audiences. 
• Experience working with modern data platforms, software engineering best practices, and data science tooling to develop scalable and maintainable analytical solutions. 
• Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), or other emerging AI technologies is advantageous.