Significant EDNY RICO Prosecution of Construction Company

Contributor on an experienced, multi-disciplinary team retained by the defense team in a high-profile Racketeer Influenced and Corrupt Organizations (RICO) prosecution in the Eastern District of New York. The role was to help integrate advanced data analytics with traditional investigative techniques to develop data-driven facts that supported the defense. This matter stemmed from federal charges related to a decade-long fraudulent overbilling scheme that allegedly impacted major public and private construction projects, including the World Trade Center Towers, the Plaza Hotel renovation, and the Javits Convention Center.

Conducted a data-driven investigation and support the legal strategy through the application of data analytics, which involved working with with legal counsel, compliance experts, and investigators to dissect the government’s allegations and uncover patterns, inconsistencies, and potential mitigating evidence embedded within years of complex construction payroll data. Utilized a combination of SQL, Python, and R to extract, transform, and analyze large volumes of structured and semi-structured data, including labor timesheets, payroll records, subcontractor invoices, and contract terms.

Using Tableau and other visualization tools, developed dynamic visualizations and dashboards that enabled the legal team to intuitively understand billing patterns, timekeeping practices, and project-level variances across different job sites and foremen. These tools were instrumental in identifying instances where alleged overbilling could be attributed to systemic practices common in the industry at the time, or to inconsistencies in client directives and contract enforcement. Also conducted trend and variance analyses to evaluate the plausibility of the government’s damage calculations and test alternative scenarios based on contractual provisions and workforce deployment norms.

A crucial component of the work involved aligning data findings with narratives from human-source interviews and established construction protocols. By triangulating quantitative analysis with qualitative insights from foremen, project managers, and client representatives, the team helped construct a more nuanced view of operational realities, billing interpretations, and labor practices. This interdisciplinary approach was vital in mounting a credible, data-supported defense.

This engagement exemplified the integration of data science, regulatory expertise, and litigation support in a complex white-collar criminal matter, with significant implications for the construction industry and corporate compliance enforcement in the U.S.