Support the development of AI-enabled products from concept through delivery, with a focus on quality, usability, scalability, and responsible implementation
Help define good practices for AI solution design, validation, monitoring, and continuous improvement
Work with cross-functional teams to identify risks, dependencies, and implementation challenges early
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Design, build, and review scalable full-stack applications, APIs, workflows, dashboards, and integrations that support AI-enabled assurance use cases
Act as the bridge between business stakeholders, product owners, AI specialists, developers, and testers to ensure delivery remains aligned, practical, and outcome-focused
Design, build, and review scalable full-stack applications, APIs, workflows, dashboards, and integrations that support AI-enabled assurance use cases
Act as the bridge between business stakeholders, product owners, AI specialists, developers, and testers to ensure delivery remains aligned, practical, and outcome-focused
Carry out both reactive and proactive data analysis of large datasets using a wide range of technologies, database management systems, business information reporting and visualisation software
Ability to execute end-to-end lifecycle of the engagement - Data extraction, transformation, loading (ETL), analysis, visualisation, deployment and client delivery
Adopt a problem-solving approach to overcome unexpected issues - both technical and operational.
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You will need to be highly motivated to succeed and have a "do whatever it takes" attitude
You will be methodical, detail minded with strong organisational skills, excellent communication skills and a proactive attitude combined with a degree of flexibility – all geared to exceeding client expectations
You will have strong problem solving, analytical and time management skills combined with exceptional communication skills.
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Carry out both reactive and proactive data analysis of large datasets using a wide range of technologies, database management systems, business information reporting and visualisation software
Develop algorithms and solutions to detect, respond, prevent, continually monitor and investigate areas of fraud, bribery & corruption, misconduct and financial crime
Develop supporting material using a suite of visualisation software to clearly present the benefits of the analysis to clients
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EY’s Forensic Data Analytics (FDA) practice is a global, data-focused team within the Forensic & Integrity Services (FIS) department. Our team supports clients in dealing with the complex issues of fraud, regulatory compliance, and business disputes.
Work with clients, fraud investigators, internal and external auditors, lawyers and regulatory authorities in sensitive situations and assist on conducting data analysis for identifying evidences of fraud, abuse and wastage.
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Carry out both reactive and proactive data analysis of large datasets using a wide range of technologies, database management systems, business information reporting and visualisation software
Develop algorithms and solutions to detect, respond, prevent, continually monitor and investigate areas of fraud, bribery & corruption, misconduct and financial crime
Develop supporting material using a suite of visualisation software to clearly present the benefits of the analysis to clients
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Help prepare reports or proposals that will be delivered to clients and other parties
Pursuing a degree in quantitative fields such as Computing, Engineering, Analytics, Statistics, Applied Mathematics, Machine Learning, Operation Research, Information Management or related fields