Senior Data Scientist - Glasgow

FDM is a global business and technology consultancy seeking a Senior Data Scientist with experience in AI and machine learning to work for our client within the finance sector. This is initially a 12-month contract with the potential to extend and will be a hybrid role that will be based in Glasgow.

Our client is seeking a Senior Data Scientist to join a new team within Global Operational Risk and Risk Oversight, focussing on developing data driven capabilities and insights to increase the breadth and depth of Operational Risk oversight. You will be responsible for developing and maintaining modern capabilities (e.g. Machine Learning Models, AI solutions, Analytical techniques) that leverage structured and unstructured data sources, to deliver enhanced risk insights to SMEs (e.g. pattern recognition, pockets of undetected risk, exception/anomaly detection, increased coverage of areas previously below the line due to resource constraints). 

As a Senior Data Scientist, you will work closely with domain specialists within Operational Risk (e.g. Cyber, Technology, Supplier, Data, Resilience), as well as colleagues in the Chief Technology Office, and AI Centre of Excellence, leveraging your expertise, to deliver data driven solutions for use cases.

Responsibilities

• Design, build, and maintain machine learning and AI models to uncover operational risk insights, including anomaly detection, pattern recognition, and risk hotspot identification
• Apply advanced statistical and analytical techniques to structured and unstructured data sources
• Develop NLP and computer vision models to extract value from text-heavy or image-based risk data (e.g., incident reports, audit findings, vendor assessments)
• Translate model outputs into actionable insights for Operational Risk SMEs, enabling the identification of emerging or undetected risks, and enhancing oversight capabilities
• Use automation and scalable analytics to provide oversight in areas previously under-monitored due to resource constraints, increasing breadth and depth of risk surveillance
• Partner with subject matter experts in domains such as Cybersecurity, Resilience, Technology, Data, and Supplier Risk to ensure models and analyses are aligned with operational risk needs
• Work closely with the Chief Technology Office and AI Centre of Excellence to ensure alignment with enterprise architecture and AI governance standards