Senior Data Scientist, Supply Chain Data Science

Starbucks is looking for a Senior Data Scientist to join its Supply Chain Data Science team in Seattle. In this role, you will apply advanced analytics and machine learning to tackle complex supply chain challenges, with responsibility spanning from early problem framing through production delivery.

The position focuses on building end-to-end data science solutions that are production-ready, including scalable data pipelines and well-engineered Python implementations. You will also collaborate with a mix of technical and non-technical stakeholders to turn modeling work into clear, actionable decisions.

What you’ll do

• Design, develop, validate, and deploy statistical and machine learning models that support supply chain decision-making, including analysis of complex supply chain data and translation into recommendations.
• Design, build, and own reliable, scalable data and model pipelines that integrate data science solutions into business and operational workflows.
• Use strong software engineering practices such as version control, code review, testing, documentation, and reproducibility.
• Communicate technical approaches, assumptions, results, limitations, and recommendations effectively to technical and non-technical stakeholders.
• Independently lead complex data science projects, including management of technical dependencies and risks, from problem definition through production delivery.
• Mentor and support other data scientists through technical guidance and code reviews.

Key skills and qualifications

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

Technologies

• Python
• SQL
• Spark
• Databricks

Preferred qualifications

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

Compensation and location

• Location: Seattle, WA (onsite)
• Salary: USD 134,700 - 219,700 per year

Benefits

• Medical, dental, and vision
• Basic and supplemental life insurance
• Other voluntary insurance benefits
• Short-term and long-term disability
• Paid parental leave
• Family expansion reimbursement
• Paid vacation
• Sick time (accrued at 1 hour for every 25 hours worked)
• Eight paid holidays
• Two personal days per year
• 401(k) retirement plan with employer match
• Discounted company stock program (S.I.P.)
• Starbucks equity program (Bean Stock)
• Incentivized emergency savings
• Financial well-being tools
• 100% upfront tuition coverage for a first-time bachelor’s degree through Arizona State University’s online program via the Starbucks College Achievement Plan
• Student loan management resources
• Access to other educational opportunities
• Backup care
• DACA reimbursement