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Federal Data Analyst

U.S. Department of Health and Human Services
New York
Estimated Salary
USD 70.000 – USD 110.000
New
Live Update
13 September 2026
Deadline
13 Sep 2027

Job Description

Join our mission-critical team as a Federal Data Analyst in New York City! We're offering an exclusive sign-on bonus of up to $10,000 for qualified candidates who can immediately contribute to vital public health initiatives. This is your opportunity to leverage advanced analytics in a secure federal environment while enjoying exceptional benefits and career stability. Why this role? You'll transform complex datasets into actionable insights that directly impact national health policies. Our collaborative culture values innovation and professional growth, with dedicated resources for continuous learning and certification support.

Responsibilities

  • Analyze and interpret large-scale federal healthcare datasets using SQL, Python, and R
  • Develop interactive visualizations and dashboards for executive decision-making
  • Ensure compliance with federal data privacy regulations (HIPAA, FISMA)
  • Collaborate with cross-agency teams on public health strategy initiatives
  • Present findings to senior leadership through clear, data-driven narratives
  • Maintain data integrity and implement robust quality control measures
  • Stay current with evolving federal data standards and methodologies

Qualifications

  • Bachelor's degree in Data Science, Statistics, Public Health, or related field
  • 3+ years of professional data analysis experience with federal datasets
  • Proficiency in SQL, Python (Pandas, NumPy), and data visualization tools
  • Strong understanding of healthcare data systems and federal reporting requirements
  • Experience with statistical modeling and predictive analytics
  • FBI security clearance eligibility or existing clearance preferred
  • Certification in data analytics (e.g., SAS, Tableau) highly desirable

Required Skills

Data Analysis SQL Python R Healthcare Data Federal Regulations Data Visualization Statistical Modeling Public Health

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