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Information Technology 🏢 Full Time ⭐️ Verified

Federal Data Analyst

U.S. Department of Homeland Security
Laredo
Estimated Salary
USD 65.000 – USD 95.000
New
Live Update
4 Oktober 2026
Deadline
4 Okt 2027

Job Description

Join our elite team at the U.S. Department of Homeland Security as a Federal Data Analyst in Laredo, TX. This critical role involves safeguarding national security through advanced data analysis and intelligence reporting. You'll work directly with federal agencies to interpret complex datasets, identify trends, and support strategic decision-making. Enjoy comprehensive benefits, professional development opportunities, and the satisfaction of serving your country.

Our Laredo office offers a dynamic environment where your analytical skills directly impact border security initiatives. We're seeking a detail-oriented professional with federal experience to join our mission-driven team.

Responsibilities

  • Analyze and interpret large-scale federal datasets to identify security threats and trends
  • Develop interactive dashboards and reports for senior leadership and agency partners
  • Ensure data integrity and compliance with federal regulations (FISMA, HIPAA, etc.)
  • Collaborate with cross-functional teams to support intelligence operations
  • Present findings through concise briefings and visual data representations
  • Maintain secure data systems and implement data governance protocols

Qualifications

  • Bachelor's degree in Data Science, Statistics, or related field (Master's preferred)
  • 3+ years experience in federal government data analysis
  • Advanced proficiency in SQL, Python, and R
  • Strong knowledge of federal data security protocols and compliance standards
  • Experience with Tableau, Power BI, or similar visualization tools
  • Certification in data analysis (e.g., CDMP, SAS) highly desirable
  • Ability to obtain and maintain a federal security clearance

Required Skills

Data Analysis SQL Python Federal Regulations Data Visualization Tableau Security Clearances Statistical Modeling

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