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