Lead Data Scientist / Data Analyst

EPAM is a leading global 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
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
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.

Work arrangement
Yes