Government-wide hiring

Data Science

In August 2020, USDS, OPM, and the Chief Data Officer council initiated the multi-agency Data Science Hiring Action Pilot using the SME-QA process. Ten federal agencies (16 components) initially participated, followed by selections from more agencies. The CDO council published the results of the action in June 2021 and the cert is available for selections until Spring 2022.

By the numbers

Participating Agencies

  1. Department of Agriculture
  2. Census Bureau
  3. Department of Commerce
  4. Consumer Financial Protection Bureau (CFPB)
  5. General Services Administration
  6. Department of Health and Human Services
  7. Department of Homeland Security
  8. Equal Employment Opportunity Commisssion
  9. National Science Foundation
  10. Office of Personnel Management
  11. Department of State
  12. Department of Transportation
  13. Department of the Treasury
  14. United States Agency for International Development
  15. Department of Veterans Affairs
Data Scientist - GS-13/14 - 0343 series
62 Vacancies
513 Applicants
107 Passed assessments (20%)
105 Selections
50 Accepted offers
Important note: selections are currently ongoing and the cert is available for selection until Spring 2022 - contact the SMEQA team for access.

Applicants

  • 513 applicants applied in two days.
  • USDS made a micro-site explaining this job.

Subject matter experts

23 data scientists from eleven agencies came together to evaluate applicants to the Data Scientist positions.

Lesson Learned: types of data people

  • Data Analysts help you understand and describe your data.
  • Data Scientists help build models to explain your data or predict things about data and outcomes you haven't seen before, and can help you scope data.
    • Some data scientists specialize in Causal Inference -- they help you understand root causes of things. They are especially good for tasks like A/B testing, social science-y questions, and power calculations.
    • Some data scientists specialize in Machine Learning -- they help you make predictions about data you haven't seen before. They are especially good at building predictive models.
    • Some data scientists are on the cutting edge of Deep Learning or Generative Modeling -- they can help with "easy for humans, hard for computers" problems, like writing an essay or drawing a picture.
  • Data Engineers help build data pipelines and data products, often for use in data science and analysis.