Senior data scientist, Supply Chain Data Science; Seattle, WA)

As a Senior Data Scientist on the Supply Chain Data Science team, you will use advanced analytics and machine learning to solve complex, high-impact supply chain problems and help improve how Starbucks plans and operates its supply chain.

This role goes beyond developing analytical models and prototypes. We are looking for a strong, hands‑on, Full Stack Data Scientist who can own data science solutions end to end, from understanding ambiguous business problems and developing analytical approaches to building production-quality code and scalable data pipelines that can be reliably deployed and maintained.

You will partner closely with data scientists, data engineers, technology teams, product partners, and supply chain business teams to translate complex problems into scalable data science solutions and measurable business impact.

As a Senior Data Scientist, you will:

• Design, develop, validate, and implement statistical and machine learning models that support supply chain decision‑making. Analyze complex supply chain data and translate findings into clear, actionable recommendations.
• Design, build, and own reliable, scalable data and model pipelines that integrate data science solutions into business and operational workflows.
• Apply strong software engineering practices, including version control, code review, testing, documentation, and reproducibility.
• Communicate technical approaches, assumptions, results, limitations, and recommendations effectively to both technical and non‑technical stakeholders.
• Independently lead complex data science projects, manage technical dependencies and risks, and drive work from problem definition through production delivery.
• Mentor and support other data scientists through technical guidance and code reviews.

We’d love to hear from people with:

• 4+ years of professional experience in data science, machine learning, applied analytics, or a closely related field.
• BA/BS or advanced degree in computer science, data science, statistics, mathematics, engineering, or another quantitative field, or equivalent practical experience.
• Strong proficiency in Python and SQL.
• Demonstrated experience developing production‑level Python code. Hands‑on experience converting data science prototypes into reliable, maintainable production solutions.
• Strong understanding of software engineering practices such as modular code design, testing, debugging, version control, documentation, and code review.
• Experience working with large and complex datasets and developing scalable data‑processing solutions.

Preferred qualifications

• MS or PhD in computer science, data science, statistics, operations research, engineering, mathematics, or a related quantitative discipline.
• Experience developing data science solutions in a supply chain, forecasting, inventory, replenishment, or planning environment.
• Experience with Spark or other distributed data‑processing technologies.
• Experience with modern cloud‑based data and machine learning platforms, such as Databricks, is preferred.
• Experience with CI/CD practices for data science or machine learning solutions.
• Experience monitoring production solutions and improving their reliability and performance over time.
• Demonstrated ability to mentor other data scientists and raise engineering and coding standards within a data science team.

As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short‑term and long‑term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked),…