Lead Data Analyst (Fraud Investigations & Data Discovery) - W2 only
Lead Data Analyst (Fraud Investigations & Data Discovery)
$50.00 on w2 wihout benefis
Amtrak 1 US - Local
Washington, DC - Remote Work
Job Description
Randstad is seeking a Lead Data Analyst to join the Enterprise Fraud Risk Management team for a major transit and infrastructure client based in Washington, DC. In this fully remote role, you will act as a foundational member of a rapidly growing program, utilizing exploratory analytics and data discovery to hunt for anomalous patterns across more than 180 identified fraud risks—including procurement, cyber, and financial statement fraud. This is an ideal opportunity for a proactive data professional who thrives in a highly dynamic, unstructured environment, enjoys building data discovery processes from scratch, and wants to directly influence how the enterprise identifies and hands off potential fraud vectors for formal investigation.
Key Responsibilities
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).
$50.00 on w2 wihout benefis
Amtrak 1 US - Local
Washington, DC - Remote Work
Job Description
Randstad is seeking a Lead Data Analyst to join the Enterprise Fraud Risk Management team for a major transit and infrastructure client based in Washington, DC. In this fully remote role, you will act as a foundational member of a rapidly growing program, utilizing exploratory analytics and data discovery to hunt for anomalous patterns across more than 180 identified fraud risks—including procurement, cyber, and financial statement fraud. This is an ideal opportunity for a proactive data professional who thrives in a highly dynamic, unstructured environment, enjoys building data discovery processes from scratch, and wants to directly influence how the enterprise identifies and hands off potential fraud vectors for formal investigation.
Key Responsibilities
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).