Lead Data Scientist / Data Analyst with Animal Healthcare background

EPAM Systems; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Healthcare benefits

Learning programs

Paid time off and sick leave

Upskilling and certification courses

LinkedIn Learning access

Global career opportunities

Volunteer opportunities

Job summary

EPAM Systems, Inc. seeks a Lead Data Scientist / Data Analyst to design and validate scalable ML solutions for health-predisposition insights from high-volume data pipelines. You will oversee deterministic-first modeling, governance, and production transition with strong documentation.

You will lead end-to-end model delivery, collaborate with SMEs, refine labels, and implement training/evaluation pipelines in Databricks with MLflow to ensure reproducibility and robust performance.

Qualifications

• 5+ years of experience in data science and ML 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.
• Strong project execution skills in fixed-scope, milestone-driven delivery with parallel tracks.
• Hands-on Python, ML skills for feature engineering, training, and evaluation workflows.

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 ML primarily for high-ambiguity scenarios.
• Define class-frequency tiers, calibrated thresholds, and evaluation plans beyond overall accuracy.
• Produce confidence scores, method traces, exception flags, and model versioning artifacts.
• Create model cards and documentation to support governance, reproducibility, and operations transfer.
• Validate performance across common, rare, ambiguous, and clinically significant cases using suitable metrics.
• Collaborate with SMEs to refine labels, interpret feedback, and adjust modeling strategies.
• Support integration into production data pipelines and contribute to stabilization and knowledge transfer.
• Implement training/evaluation pipelines in Databricks with MLflow tracking and reproducible builds.

Skills

Python

ML model development

Data analysis

Feature engineering

Databricks

MLflow

NLP

Tools

Databricks

MLflow

Python

Job description

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.ResponsibilitiesLead design and delivery of optimized models for species, gender, breed, weight classification, and age classificationBuild health-predisposition insights models using standardized signalment attributes and governed ontologiesApply a deterministic-first approach and use machine learning primarily for high-ambiguity scenariosDefine class-frequency tiers, calibrated thresholds, and evaluation plans that go beyond overall accuracyProduce confidence scores, method traces, exception flags, and model versioning artifacts for each modelCreate model cards and documentation that support governance, reproducibility, and transition to operationsValidate performance across common, rare, ambiguous, and clinically significant cases using appropriate classification metricsIncorporate animal-health domain knowledge into life-stage thresholds, breed-dependent reference ranges, and risk mappingsImplement training and evaluation pipelines in Databricks with MLflow tracking and reproducible buildsCollaborate with SMEs to refine labels, interpret validation feedback, and adjust modeling strategiesSupport integration into production data pipelines and contribute to stabilization and knowledge transferRequirements5+ years of experience in data science and machine learning for classification problemsHands-on experience building hybrid deterministic + ML solutions for ambiguous casesLead-level ownership of end-to-end model delivery from prototyping through stabilization and knowledge transferStrong project execution skills in fixed-scope, milestone-driven delivery with multiple parallel model tracksHands-on Python.ML skills for feature engineering, training, and evaluation workflowsDatabricks and MLflow experience for reproducible training, evaluation, and model versioningComputer vision and natural language processing experience to support fuzzy matching and embedding-based approachesOMOP Common Data Model knowledge and SNOMED CT Veterinary Extension concept-mapping experienceStrong analytical skills to define class-frequency tiers, calibrated risk bands, and performance thresholdsStrong communication skills to interpret annotation and validation plans with domain SMEs and translate them into model updatesAdvanced English proficiency (C1+ level)Nice to haveExpertise with classification metrics for imbalanced data such as PR AUC, F1 by class, and balanced accuracyExperience using calibrated probability and reliability diagrams to assess confidence scoresAbility to set per-tier metric targets and acceptance criteria for rare and clinically significant classesWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn