Cybersecurity Analytics Lead

<p class="p1">At <strong>Ardent</strong>, we hire people who want more than a job — they want to serve a mission that matters. Our teams support the federal government’s most critical national security and defense priorities, helping protect the nation, strengthen resilience, and advance the technologies and capabilities that keep America secure. For veterans, cleared professionals, and purpose-driven innovators, Ardent is a place to continue serving alongside a team that understands the importance of the mission and the people behind it.</p> <p class="p1">We also know top talent has choices, which is why we back our mission with benefits and flexibility that stand out: competitive pay, comprehensive health coverage, flexible PTO, federal holidays off, tuition reimbursement, professional development support, wellness stipends, and a culture that values and rewards hard work, dedication, and adaptability. If you want to build something meaningful, while enjoying the kind of flexibility and support that you need to do your best work — <strong>Ardent</strong> is where your next mission begins.</p> <hr> <p><strong>Ardent</strong> is seeking a&nbsp;<strong>Cybersecurity Analytics Lead</strong>&nbsp;to join our team.&nbsp;&nbsp;</p> <p>This is&nbsp;an on-site position in Lanham, MD.</p> <p><strong><u>Position Description:</u></strong></p> <p>Ardent is seeking a Cybersecurity Analytics Lead to support the IRS Cybersecurity Fraud Analytics and Monitoring (CFAM) program through fraud analytics operations, predictive analysis, forensic investigations, and cybersecurity monitoring activities. This role will support large-scale analytics initiatives focused on detecting anomalous, malicious, and fraudulent activity across IRS online application ecosystems.</p> <p><strong><span style="text-decoration: underline;">Responsibilities and Duties:</span></strong></p> <ul data-spread="false"> <li>Support fraud analytics, predictive analytics, and forensic analysis activities across enterprise environments.</li> <li>Conduct analysis of structured and unstructured data to identify suspicious or anomalous activity.</li> <li>Support implementation and enhancement of analytical models and fraud detection methodologies.</li> <li>Perform log analysis, data correlation, and investigation of cybersecurity or fraud-related events.</li> <li>Assist with development of analytical reports, briefings, and operational documentation.</li> <li>Support incident response and mitigation activities related to fraudulent or malicious activity.</li> <li>Collaborate with stakeholders to support data ingestion, ETL processes, and analytics platform enhancements.</l