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.</li> <li>Participate in development of fraud indicators, predictive models, and machine learning-based analytics.</li> <li>Support continuous monitoring and analysis of IRS application ecosystems.</li> <li>Assist with operational planning, technical analysis, and coordination activities.</li> </ul> <p><span style="text-decoration: underline;"><strong>Requirements:&nbsp;</strong></span></p> <ul data-spread="false"> <li>Bachelor’s degree in Cybersecurity, Computer Science, Information Technology, Data Science, Engineering, Mathematics, Statistics, or related field, or equivalent demonstrated experience.</li> <li>Minimum of 5 years of experience supporting cybersecurity operations, fraud analytics, data analytics, or enterprise monitoring environments.</li> <li>Experience supporting cybersecurity monitoring, fraud detection, or incident response activities.</li> <li>Experience conducting log analysis, data analysis, or investigative activities.</li> <li>Ability to analyze data and identify suspicious or anomalous patterns.</li> <li>Familiarity with cybersecurity monitoring tools, analytics platforms, or SIEM technologies.</li> <li>Strong written and verbal communication skills.</li> <li>Ability to work independently and support multiple operational priorities.</li> </ul> <p><span style="text-decoration: underline;"><strong>Preferred Qualifications:&nbsp;</strong></span></p> <ul data-spread="false"> <li>Experience supporting IRS, Treasury, Federal Civilian, Intelligence Community, or regulated environments.</li> <li>Familiarity with machine learning, predictive analytics, or fraud analytics concepts.</li> <li>Experience with tools such as Splunk, ElasticSearch, Python, R, SQL, Spark, or similar technologies.</li> <li>Experience supporting ETL processes, data ingestion, or analytics platform operations.</li> <li>Familiarity with cybersecurity incident response and forensic analysis activities.</li> <li>Experience supporting enterprise cybersecurity or fraud monitoring programs.</li> </ul> <p>Due to the nature of the work we support, all candidates in consideration for this role must be willing to undergo the government issued background investigation process. We highly encourage all Veterans and those with disabilities to apply.</p> <hr> <p><strong>Ardent </strong>is an equal opportunity employer. We will not discriminate in employment, recruitment, advertisements for employment, compensation, termination, upgrading, promotions, and other conditions of employment against any employee or job applicant on the bases of race, color, gender, national origin, age, religion, creed, disability, veteran's status, sexual orientation, gender identity, gender expression, or any other basis protected by state, local, or federal law.</p>