Control testing- Data Analytics

Role & responsibilities

• Support development of data-driven control monitoring solutions, to improve Control Monitoring efficiency and visibility of outcomes.
• Develop and maintain interactive dashboards and reporting outputs to support control monitoring, providing clear, data-driven insights into control performance, exceptions and emerging risk trends.
• Apply data analytics to execute control testing activities, ensuring outputs are accurate, reliable and aligned with established methodologies and quality standards.
• Support the enhancement of control testing and quality assurance processes through improved use of data, analytics and standardised approaches.
• Assist in the automation of manual testing processes, contributing to increased efficiency, scalability and consistency of assurance activities.
• Apply automation and emerging AI capabilities (where appropriate) to improve testing coverage, enable more targeted testing of higher-risk areas and support uplift of the control environment.
• Analyse datasets to identify control weaknesses, exceptions, and risk indicators, escalating findings and supporting interpretation under guidance from senior team members.
• Support the translation of analytical outputs into insights, contributing to identification of control testing priorities and improvement opportunities.
• Contribute to quality assurance and validation activities, including testing logic, data accuracy and completeness of outputs.
• Identify and highlight data gaps or limitations in testing coverage, supporting initiatives to improve data quality and expand assurance scope.
• Drive efficiency across high-volume control testing activities, enabling better prioritisation and focus on key risk areas.
• Collaborate effectively with business, risk and technology stakeholders to support the delivery of control testing and monitoring outcomes.

Preferred candidate profile

• Advanced capability in data analytics, automation, and R programming, including handson experience building R Shiny applications and scalable, productionready solutions for control testing.
• Knowledge in control testing methodologies and operational risk assurance, with experience overseeing testing quality and delivering effective outcomes.
• Ability to work with structured and moderately complex datasets to generate insights.
• Knowledge of nonfinancial risk frameworks, governance and regulatory requirements, with a focus on documentation and evidencing standards.
• Effective communication skills, with ability to present findings clearly to stakeholders.
• Good time management and organizational skills, with ability to deliver within deadlines.