Note: The job is a remote job and is open to candidates in USA. PLANET.TECH is a deep-tech climate hardware company focused on developing a non-invasive biometric monitoring platform for cattle. The Veterinary Data Scientist will bridge clinical veterinary knowledge and data science to build disease-detection algorithms from physiological data, turning raw biometric signals into meaningful health insights.
Responsibilities
- Design and lead the data labeling pipeline: define clinical event categories, build labeling protocols, train and manage contract labelers
- Review sensor data against clinical outcomes to build ground-truth datasets for disease detection model training
- Collaborate with ML engineers on feature engineering, model evaluation, and clinical validation of detection algorithms
- Mine veterinary literature and epidemiological research to inform algorithm design and detection thresholds
- Support field validation studies: define study protocols (ARRIVE 2.0 / STARD compliant), analyze results, contribute to peer-reviewed publications
- Serve as the veterinary subject-matter expert across the data pipeline — ensuring that what the models detect is clinically real and defensible
Skills
- DVM, VMD, or equivalent veterinary degree (or PhD in veterinary epidemiology, animal science, or a closely related field)
- Large-animal clinical experience or research focus (beef and/or dairy cattle strongly preferred)
- Demonstrated comfort with data: you've worked with datasets, statistical analysis, or computational tools beyond what's typical in clinical practice
- Familiarity with or strong interest in machine learning concepts, particularly time-series classification, signal processing, or biomedical data analysis
- Published or peer-reviewed research experience (doesn't have to be in data science — we're looking for the research mindset)
- Ability to work across disciplines: you can explain clinical nuance to engineers and translate model outputs back into veterinary relevance
- Experience with wearable sensor data, precision livestock farming (PLF), or veterinary informatics
- Python, R, or SQL proficiency
- Experience with study design for diagnostic accuracy (sensitivity/specificity, ROC analysis)
- Familiarity with bovine respiratory disease (BRD), parasitic conditions, or acute disease presentations in cattle
- Experience labeling or annotating biomedical data for ML training
- Connections in the bovine veterinary research community
Benefits
- Equity: Meaningful early-stage-team equity grant. This is a ground-floor position — your equity reflects that.
- Full-time conversion: As the company scales, conversion to full-time W-2 with competitive salary
- Remote-flexible for the right candidate
- Periodic travel to field sites required
Company Overview