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AI Risk Comparison

Software Quality Assurance Analysts and Testers vs Biostatisticians

Compare AI replacement risk, automatable work, resilient skills, and potential career pivots for both occupations.

Safer role
Software Quality Assurance Analysts and Testers
Higher risk
Biostatisticians
Risk gap
0 points
TechnologyO*NET: 15-1253.00

Software Quality Assurance Analysts and Testers

Develop and execute software tests to identify software problems and their causes. Test system modifications to prepare for implementation. Document software and application defects using a bug tracking system and report defects to software or web developers. Create and maintain databases of known defects. May participate in software design reviews to provide input on functional requirements, operational characteristics, product designs, and schedules.

AI Risk Score

58/100
Medium

Moderate risk: AI can reshape important parts of the role.

Automation factors

  • Identify, analyze, and document problems with program function, output, online screen, or content.
  • Document software defects, using a bug tracking system, and report defects to software developers.
  • Develop testing programs that address areas such as database impacts, software scenarios, regression testing, negative testing, error or bug retests, or usability.
  • Working with Computers
  • Processing Information

Top skills

Reading Comprehension4.00/5
Active Listening3.88/5
Speaking3.88/5
Critical Thinking3.88/5
Writing3.75/5

Recommended career pivots

Software Developers55/100Validation Engineers50/100Computer Systems Engineers/Architects51/100Penetration Testers6/100Computer Systems Analysts44/100
TechnologyO*NET: 15-2041.01

Biostatisticians

Develop and apply biostatistical theory and methods to the study of life sciences.

AI Risk Score

58/100
Medium

Moderate risk: AI can reshape important parts of the role.

Automation factors

  • Draw conclusions or make predictions, based on data summaries or statistical analyses.
  • Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.
  • Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
  • Analyzing Data or Information
  • Working with Computers

Top skills

Mathematics4.62/5
Reading Comprehension4.00/5
Speaking4.00/5
Science4.00/5
Critical Thinking4.00/5

Recommended career pivots

Data Scientists8/100Statisticians67/100Bioinformatics Scientists41/100Clinical Data Managers63/100Bioinformatics Technicians64/100

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