Audit & Risk Recruitment
Technology Controls - AI & Analytics Manager
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Audit & Risk Recruitment is working with a FTSE 100 diversified business to help them find a Data Analytics and AI Manager for their Technology Controls team.
Strengthening the Group's internal control environment is a priority for management and the Board of the company. The Group Internal Controls team was established to address key finance control priorities and controls over the IT environment, which include both general IT and segregation of duties controls.
This is a high-profile role within the business. The ideal candidate is comfortable in operating in an environment where there isn’t a pre-existing “playbook”, putting their experience into practice to closely work with the business to achieve practical, pragmatic and sustainable improvements in internal controls.
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The role holder will lead the advancement of the organisation’s use of AI & Analytics tools to meet control requirements and implement all the tools, techniques, and resources to ensure these are met sustainably.
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The ideal candidate for this position will have prior experience of delivering AI & Analytics solutions in the internal audit and internal control fields for a large corporation or as a consultant with a top-tier practice firm.
Responsibilities
- Identify and implement AI & Analytics opportunities to strengthen controls, leverage technologies to help the business achieve compliance efficiently, and improve the speed and quality of monitoring and reporting by the Internal Controls team. This will include:
- Developing and deploying analytics scripts and solutions (e.g., Python and ACL) to automate reviews (e.g., flagging exceptions and facilitating resolution), also leveraging continuous control monitoring capabilities of the Diligent platform, and further customise Diligent robotics to evolving needs (handover from Diligent developers will be provided).
- Identifying, designing, and implementing AI solutions to educate and train the business on regulatory and internal policy requirements, and streamline reviews by analysing large, complex datasets against predefined expectations.
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