EPAM is a leading general provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

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