Cybersecurity Analytics Lead

Ardent•Washington, DC

2d•Onsite

About The Position

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.

Requirements

Bachelor’s degree in Cybersecurity, Computer Science, Information Technology, Data Science, Engineering, Mathematics, Statistics, or related field, or equivalent demonstrated experience.
Minimum of 5 years of experience supporting cybersecurity operations, fraud analytics, data analytics, or enterprise monitoring environments.
Experience supporting cybersecurity monitoring, fraud detection, or incident response activities.
Experience conducting log analysis, data analysis, or investigative activities.
Ability to analyze data and identify suspicious or anomalous patterns.
Familiarity with cybersecurity monitoring tools, analytics platforms, or SIEM technologies.
Strong written and verbal communication skills.
Ability to work independently and support multiple operational priorities.
Willingness to undergo the government issued background investigation process.

Nice To Haves

Experience supporting IRS, Treasury, Federal Civilian, Intelligence Community, or regulated environments.
Familiarity with machine learning, predictive analytics, or fraud analytics concepts.
Experience with tools such as Splunk, ElasticSearch, Python, R, SQL, Spark, or similar technologies.
Experience supporting ETL processes, data ingestion, or analytics platform operations.
Familiarity with cybersecurity incident response and forensic analysis activities.
Experience supporting enterprise cybersecurity or fraud monitoring programs.

Responsibilities

Support fraud analytics, predictive analytics, and forensic analysis activities across enterprise environments.
Conduct analysis of structured and unstructured data to identify suspicious or anomalous activity.
Support implementation and enhancement of analytical models and fraud detection methodologies.
Perform log analysis, data correlation, and investigation of cybersecurity or fraud-related events.
Assist with development of analytical reports, briefings, and operational documentation.
Support incident response and mitigation activities related to fraudulent or malicious activity.
Collaborate with stakeholders to support data ingestion, ETL processes, and analytics platform enhancements.
Participate in development of fraud indicators, predictive models, and machine learning-based analytics.
Support continuous monitoring and analysis of IRS application ecosystems.
Assist with operational planning, technical analysis, and coordination activities.