Statistical Analyst V – SAS, Dashboards & Court Data

Arizona Supreme Court

Phoenix (AZ)

On-site

USD 52,000 - 70,000

Full time

2 days ago
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Benefits offered by this job

Health insurance
Retirement plan
Paid holidays

Job summary

Arizona Supreme Court seeks a Jr. Statistical Analyst V to support statewide reporting through data collection, validation, and maintenance of statistical and survey data.

You will process datasets and reporting interfaces in SAS, maintain webpages and dashboard content, and assist courts with reporting requirements and statistical inquiries. The role collaborates with stakeholders, develops testing scenarios, and may provide onsite or virtual training on data submission processes.

Qualifications

  • Requires degree in criminal justice, social science, or related field with coursework in research methods, statistics, or database management.
  • Minimum of three years of applied statistical research or relational database experience.
  • Proficiency with statistical analytic software and understanding database structures.

Responsibilities

  • Support statewide reporting through data collection, validation, and maintenance of statistical and survey data.
  • Process datasets and reporting interfaces in SAS.
  • Maintain webpages and dashboard content; assist courts with reporting requirements and statistical inquiries.
  • Collaborate with internal and external stakeholders; develop testing scenarios and provide training on data submission processes.

Education

Degree in criminal justice or social science

Tools

SAS

Job description

Arizona Supreme Court seeks a Jr. Statistical Analyst V to support statewide reporting through data collection, validation, and maintenance of statistical and survey data.

You will process datasets and reporting interfaces in SAS, maintain webpages and dashboard content, and assist courts with reporting requirements and statistical inquiries. The role collaborates with stakeholders, develops testing scenarios, and may provide onsite or virtual training on data submission processes.

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