Senior Data Scientist, Supply Chain — End-to-End ML

Starbucks; Seattle (WA); Presencial; USD 140 000 - 210 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Medical, dental, vision insurance

Life insurance

401(k) with employer match

Tuition coverage

Resumo da oferta

Starbucks is seeking a Senior Data Scientist for the Supply Chain Data Science team in Seattle. You will tackle high-impact supply chain problems using advanced analytics and ML, delivering end-to-end production-quality solutions that scale in a global business.

You will lead data science projects, build pipelines, and collaborate with data engineers, tech teams, and business partners to translate complex problems into measurable business impact while mentoring peers.

Qualificações

• BA/BS or higher in CS, data science, engineering, or quantitative field.
• Strong Python and SQL with production code experience.
• Experience handling large, complex datasets.
• Knowledge of software engineering practices (modular code, testing, version control, docs).

Responsabilidades

• Design, develop, validate, and implement ML models for supply chain decisions.
• Build reliable, scalable data and model pipelines integrated into workflows.
• Apply software engineering practices: version control, testing, documentation, reproducibility.
• Communicate approaches and results to technical and non-technical stakeholders.
• Lead complex data science projects from problem definition to production delivery.
• Mentor and support other data scientists.

Conhecimentos

Python

SQL

Data science

Software engineering

Mentoring

Formação académica

BA/BS in CS/Data Science/Engineering

MS/PhD in related field

Ferramentas

Spark

Databricks

CI/CD

Cloud platforms

Descrição da oferta de emprego

Starbucks is seeking a Senior Data Scientist for the Supply Chain Data Science team in Seattle. You will tackle high-impact supply chain problems using advanced analytics and ML, delivering end-to-end production-quality solutions that scale in a global business.

You will lead data science projects, build pipelines, and collaborate with data engineers, tech teams, and business partners to translate complex problems into measurable business impact while mentoring peers.