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With over 30 years as a management accountant and financial systems specialist, I bring deep domain expertise in translating complex real-world financial processes into structured, high-integrity datasets — the exact skill set required for high-quality AI training and validation in accounting, tax, reconciliation, forecasting, and financial close workflows. Although my background is not in generic data labelling, I have extensive hands-on experience designing, implementing, migrating, and validating large-scale accounting and reporting environments across regulated industries. This includes full-cycle data mapping, reconciliation, integrity checks, and process documentation for ERP systems such as Oracle JD Edwards, Microsoft Dynamics 365, TM1/IBM Cognos, SAP, and Navision. I am currently producing independent, in-depth appraisals of how AI models perform against actual accounting standards and practical business realities, giving me direct, ongoing exposure to evaluating and refining AI outputs in finance.What sets me apart is my ability to rapidly learn any financial system or tool and convert practical accounting knowledge into AI-ready training data. I have led major projects including capital expenditure modelling on a £1 billion infrastructure build, group reporting rebuilds for £150m+ portfolios, full D365 implementations with user acceptance testing, and large-scale data flows into Navision and TM1 cubes. My work consistently focuses on ensuring data accuracy, regulatory compliance, and audit-ready integrity — precisely the quality control and domain validation that AI companies need for specialised financial models.
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Contract Management Accountant & Financial Systems Specialist