20 tasks, each one witnessed by the sources that watched the job — and behind every one, a prompt you can use tonight.
You might start by checking animals — observing behavior, recording feed intake, or looking for health signs. Mornings often include managing animal groups (herding, moving pens) and applying biosecurity steps like boot disinfection and record checks.
Afternoons often include data work: entering observations into Microsoft Excel or SQL databases, running basic stats in SAS, and meeting farmers or technicians. Some days focus on experiments in physiology or breeding, or supervising staff and coordinating embryo transfer or drug administration for breeding.
Expect Microsoft Word and PowerPoint for reports and presentations, and Excel for spreadsheets of feed, weight, or behavior records. If you do research, you’ll use SAS for statistical analysis and possibly Tableau for visualizing results.
If you manage larger databases or integrate devices, you’ll see SQL. For genetic evaluations you might use BLUP (Best Linear Unbiased Prediction) software to estimate breeding values.
The U.S. Bureau of Labor Statistics (BLS) reports about 3,100 employed in this SOC code. The median pay is $68,940 per year, the lowest tenth is $44,350, and the top tenth is $166,000, according to BLS (2025).
Pay varies by employer: university researchers, private agribusiness, or veterinary clinics may differ. Grants, publication record, and management responsibilities often push pay higher.
A bachelor’s in animal science, biology, or veterinary technology is typical; many roles expect a master’s or PhD for independent research. Focus on courses in animal physiology, genetics, and microbiology, plus statistics and SQL or Excel skills.
Get hands-on experience with farm animals, labs, or clinics. Volunteer on farms, assist with breeding programs (embryo transfer, reproductive drug protocols), or help a research group with data entry and SAS analysis.
AI can help with video behavior scoring, pattern detection, or automating data cleaning from Excel or SQL exports. Use AI to assist, not replace, validation: always check AI outputs against human-scored samples and keep raw data files.
Protect sensitive data and biosecurity info. Don’t upload identifiable farm or animal health records to public AI services. Use local or approved platforms and document any AI step in methods for reproducibility.
Strong observational skills with animals, plus practical management (feeding, welfare, biosecurity) are essential. You must design experiments, run statistical analyses in SAS or Excel, and interpret BLUP genetic results.
Communication matters: write clear reports in Word, make presentations in PowerPoint, and collaborate with farmers and staff. Supervisory skills and basic SQL or Tableau for data handling help you run projects.