Lead Data Scientist / Data Analyst

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 with multiple parallel model tracks - Hands-on Python.ML skills for feature engineering, training, and evaluation workflows - Databricks and MLflow experience for reproducible training, evaluation, and model versioning - Computer vision and natural language processing experience to support fuzzy matching and embedding-based approaches - OMOP Common Data Model knowledge and SNOMED CT Veterinary Extension concept-mapping experience - Strong analytical skills to define class-frequency tiers, calibrated risk bands, and performance thresholds - Strong communication skills to interpret annotation and validation plans with domain SMEs and translate them into model updates - Advanced English proficiency (C1+ level)

Nice to have

- Expertise with classification metrics for imbalanced data such as PR AUC, F1 by class, and balanced accuracy - Experience using calibrated probability and reliability diagrams to assess confidence scores - Ability to set per-tier metric targets and acceptance criteria for rare and clinically significant classes

We offer

- International projects with top brands - Work with global teams of highly skilled, diverse peers - Healthcare benefits - Employee financial programs - Paid time off and sick leave - Upskilling, reskilling and certification courses - Unlimited access to the LinkedIn Learning library and 22,000+ courses - Global career opportunities - Volunteer and community involvement opportunities - EPAM Employee Groups - Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn