Senior Data Scientist, Supply Chain: End-to-End ML & Analytics

Starbucks Corp.; Seattle (WA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) matching

Tuition coverage

Life insurance

Job summary

Starbucks Coffee Company is seeking a Senior Data Scientist for the Supply Chain Data Science team to solve complex analytics problems and improve planning and operations. You will own data science solutions end‑to‑end, from problem framing to production‑quality code and scalable data pipelines.

You will design and implement ML models, build data pipelines, and collaborate with data scientists, engineers, product partners, and business teams to deliver measurable impact.

Qualifications

• 4+ years of professional experience in data science, machine learning, analytics, or related field.
• Strong proficiency in Python and SQL.
• Experience developing production‑level Python code and scalable data pipelines.
• Solid understanding of software engineering practices: modular code, testing, version control, documentation.
• Experience working with large and complex datasets and scalable data processing.

Responsibilities

• Design, develop, validate, and implement statistical and ML models for supply chain decisions.
• Build reliable, scalable data and model pipelines integrated into workflows.
• Apply software engineering practices with version control, testing, and documentation.
• Communicate approaches, results, and recommendations to technical and non‑technical stakeholders.
• Lead complex data science projects end-to-end and manage risks and dependencies.
• Mentor and review work of other data scientists.

Education

BA/BS or advanced degree in computer science, data science, statistics, mathematics, engineering, or related quantitative field

MS or PhD in related quantitative discipline

Tools

Python

SQL

Databricks

Spark

CI/CD for data science

Job description

Starbucks Coffee Company is seeking a Senior Data Scientist for the Supply Chain Data Science team to solve complex analytics problems and improve planning and operations. You will own data science solutions end‑to‑end, from problem framing to production‑quality code and scalable data pipelines.

You will design and implement ML models, build data pipelines, and collaborate with data scientists, engineers, product partners, and business teams to deliver measurable impact.