Data Scientist Team Lead (R-00230)

True Zero Technologies, a veteran-owned small business, was founded on the principle that the purposeful enablement of people and technology in an organization directly ties to the quality of its outcomes. True Zero recognizes that those outcomes begin and end with our people, and that is what we have built a community of like-minded, driven, and passionate individuals and innovators who are aligned in a common goal of delivering top-tier services to our customers. Our culture and commitment have been recognized through numerous accolades, including being named one of the Best Places to Work in 2023 in two categories (“Prosperous and Thriving” ($5MM-$50MM in gross revenue) and “Mid-Atlantic Region” (DC, DE, MD, NC, VA, WV)), and again in 2025 as a Best Places to Work honoree. In addition, True Zero earned coveted spots on the Inc. 5000 list of fastest-growing companies in America in 2022, 2023, and 2025, a testament to our sustained growth driven by our people-first approach and unwavering dedication to excellence.

This role will serve as a senior technical resource responsible for developing data

models, machine learning capabilities, analytical workflows, and cybersecurity automation

across large and disparate enterprise data sets. The role will work closely with Security

Operations Center personnel, cyber threat hunters, cyber threat intelligence analysts, penetration

testers, digital forensics personnel, and cybersecurity engineers to transform security telemetry

and threat intelligence into actionable defensive capabilitie

Job Responsibilities

• Lead the design and implementation of technical data science solutions supporting enterprise

  cybersecurity operations.

• Develop data models and automation capabilities that enhance security monitoring, detection,

  threat hunting, UEBA, and correlation of cybersecurity information across the ICE enterprise.

• Design and implement custom algorithms, analytical processes, and data architectures for

  complex enterprise scale data sets used for modeling, data mining, research, and cyber defense.

• Develop advanced analytical capabilities supporting predictive risk analysis, risk identification, risk

  mapping, cyber risk cost analysis, supply chain threat identification, and User and Entity Behavior

  Analytics.

• Design data pipelines and workflows that ingest, normalize, correlate, and analyze information from

  multiple disparate security and enterprise data sources.

• Develop machine learning algorithms and models to identify anomalous behavior, emerging cyber

  threats, attack patterns, and other indicators of malicious activity.

• Develop metrics and trending analysis covering enterprise security anomalies, threat actor activity

  and impact, user behavior anomalies, and other relevant cybersecurity data.

• Apply data science and automation to cyber threat hunting activities to increase analytical maturity

  and reduce manual investigative processes.

• Incorporate data science modeling into operational threat hunting and support predictive threat

  simulations designed to estimate cyber attack probability and potential cost or impact.

• Develop capabilities that correlate cyber threat intelligence with assets, users, and security events

  to evaluate the potential financial and operational impact of cyber incidents.

• Support development of custom Indicators of Compromise and Indicators of Attack detection and

  alerting mechanisms.

• Develop visualizations, dashboards, and other high visibility reporting capabilities that

  communicate complex cybersecurity data, trends, risks, and analytical findings to technical and

  leadership audiences.

• Design and develop automation supporting security tool administration, cybersecurity analytics,

  customized searches, and security applications.

• Support integration of analytical capabilities with Security Information and Event Management and

  Security Orchestration, Automation, and Response platforms.

• Support ICE User and Entity Behavior Analytics capabilities and the development, integration,

  optimization, and maintenance of security data analytics capabilities.

• Identify and resolve critical data quality, integrity, architecture, and analytical issues affecting

  cybersecurity capabilities.

• Support development of repeatable and scalable analytical processes that improve detection,

  investigation, response, and proactive defense operations.

Job Qualifications

• Master’s or PhD degree in a quantitative field such as Statistics, Engineering, Computer Science, or

Economics required, OR additional experience above the minimum may be considered in lieu of the

required education on a year for year basis.

• 5+ years of experience with machine learning engineering, data science, data project engineering, or

software development for data solutions.

• Experience with designing a technical solution and leading a team in the implementation of the

technical design.

• Experience with object oriented programming languages such as Python, JSON, C++, Java, R, or Scala.
• Experience with containerization tools, including Kubernetes and Docker.
• Experience with architecting and designing novel analytic methods using machine learning

methodologies.

• Experience with developing and supporting data oriented tasks for cybersecurity solutioning,

including developing machine learning algorithms, data models, or architecture strategy for cyber

defense purposes.

• Experience with developing and engineering data workflows to merge disparate data sources and

draw data driven insights.

• Experience with designing and developing automation for security tools management and creating

customized searches and applications

• Ability to support high visibility reporting on cybersecurity data through development of data

visualizations and/or dashboards.

• Must possess at least a Certified Analytics Professional (CAP) certification and be eligible for a Secret clearance.