We are seeking a Lead Data Scientist / Data Analyst to design, validate, and integrate scalable ML solutions that standardize clinical signalment attributes and generate health-predisposition insights in high-volume data pipelines. You will lead deterministic-first modeling, rigorous evaluation, and production transition with strong documentation and governance.

Responsibilities

• Lead design and delivery of optimized models for species, gender, breed, weight classification, and age classification
• Build health-predisposition insights models using standardized signalment attributes and governed ontologies
• Apply a deterministic-first approach and use machine learning primarily for high-ambiguity scenarios
• Define class-frequency tiers, calibrated thresholds, and evaluation plans that go beyond overall accuracy
• Produce confidence scores, method traces, exception flags, and model versioning artifacts for each model
• Create model cards and documentation that support governance, reproducibility, and transition to operations
• Validate performance across common, rare, ambiguous,



and clinically significant cases using appropriate classification metrics
• Incorporate animal-health domain knowledge into life-stage thresholds, breed-dependent reference ranges, and risk mappings
• Implement training and evaluation pipelines in Databricks with MLflow tracking and reproducible builds
• Collaborate with SMEs to refine labels, interpret validation feedback, and adjust modeling strategies
• Support integration into production data pipelines and contribute to stabilization and knowledge transfer

Requirements

• 5+ years of experience in data science and machine learning for classification problems
• Hands-on experience building hybrid deterministic + ML solutions for ambiguous cases
• Lead-level ownership of end-to-end model delivery from prototyping through stabilization and knowledge transfer
• Strong project execution skills in fixed-scope, milestone-driven delivery wit

📌 Lead Data Scientist (Chile)
🏢 EPAM Systems
📍 Chile