Peter Millar

Peter Millar

Senior Data Scientist

Research Triangle Park, NC · Senior

Sponsorship not specifiedDetected 34 days ago
PythonSQLAzureCloud PlatformsMachine LearningData EngineeringData ScienceData VisualizationNLPLLMsRAGAgentic AIA/B TestingForecastingResearchLeadershipCommunicationCollaborationMentoringDemand Planning

About the role

  • It's fun to work in a company where people truly BELIEVE in what they're doing!
  • We're committed to bringing passion and customer focus to the business.
  • The Senior Data Scientist expands Peter Millar's data science capacity beyond customer analytics, owning forecasting, merchandising, and operations modeling.

Nice to have

  • Microsoft Fabric - hands-on experience deploying models in the Fabric Data Science workload (notebooks, MLflow, model registry).
  • OneLake. experience accessing and engineering features from OneLake (Lakehouse, Delta tables, shortcuts).
  • Programming. strong Python and SQL with production-level coding experience.
  • Experience with BI tools (Power BI preferred) and exposure to GenAI/NLP use cases is a plus.
  • Strong proficiency in Python and SQL with production-level coding experience.
  • Hands-on experience deploying models in cloud environments (Microsoft Fabric/Azure preferred).
  • Strong foundation in statistical methods including regression, classification, clustering, and time series.
  • Experience translating analytical outputs into business insights for non-technical stakeholders.

Skills

  • Establish and enforce best practices for code quality, version control, model documentation, and reproducibility.
  • Translate ambiguous business problems into well-scoped analytical projects with clear deliverables.
  • Foster a culture of continuous learning, feedback, and technical excellence.
  • Present complex technical findings to non-technical audiences in a clear and compelling manner.
  • Leverage external and group-level resources to enhance analytical capabilities and benchmarks.
  • Conduct deep-dive analyses combining internal and external data sources to generate actionable consumer insights.
  • Stay current on advancements in machine learning, AI, and consumer analytics.
  • Establish guardrails for responsible AI usage, including validation, explainability, and cost management.
  • Identify and scale high-value AI use cases across the business.

This listing is sourced directly from Peter Millar's careers page and normalized into a canonical job model.