Perform deep-dive exploratory analytics and data discovery to identify anomalies, trends, and potential indicators of internal and external fraud.
Partner closely with Digital Technology (DT) and Governance, Risk, and Compliance (GRC) teams to design and implement technological fraud solutions.
Build, define, and refine unstructured data processes to establish clean workflows and robust documentation for potential fraud handoffs.
Actively provide feedback and strategic recommendations on analytical paths, adapting strategies fluidly when data models or discovery directions need pivot.
Collaborate with stakeholders across procurement, cyber, and finance to map data structures to enterprise-wide fraud risks.
Qualifications
Proven mid-to-senior level experience in data analytics, data discovery, and advanced data mining.
Strong experience working with fraud analytics, anomaly detection, or forensic data analysis (e.g., procurement fraud, cyber fraud, or financial statement analysis).
Demonstrated ability to work independently and maintain high performance in an ambiguous, "greenfield" program environment.
Excellent communication skills with the confidence to propose new methodologies and voice feedback to leadership.
Prior experience in the construction industry or large-scale asset-intensive sectors is highly preferred (though broad industry experience is welcome)