Question
FULL_TIME
5-10

senior decision scientist, Quantitative Science

12/2/2025

Develop causal inference and experimentation frameworks to quantify the impact of operational or assortment changes. Collaborate with cross-functional teams to achieve successful outcomes in various projects.

Working Hours

40 hours/week

Company Size

10,001+ employees

Language

English

Visa Sponsorship

No

About The Company
At Starbucks, we like to say that we are not in the coffee business serving people, but in the people business serving coffee. Here, our employees - who we call partners – are the heart of the Starbucks experience, and being a partner means aspiring to become part of something bigger: inspiring positive change in the world and growing in your career and in your community. ​ It’s an opportunity to be your personal best. ​ Starbucks is an equal opportunity employer of all qualified individuals, including minorities, veterans and individuals with disabilities.​​ In everything we do, we are dedicated to our mission: To be the premier purveyor of the finest coffee in the world, inspiring and nurturing the human spirit — one person, one cup and one neighborhood at a time. Join us. Inspire with every cup. Explore opportunities, benefits and more at careers.starbucks.com
About the Role
Develop causal inference and experimentation frameworks to quantify the impact of operational or assortment changes All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law. Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances. Experience with forecasting, inventory optimization, and supply chain planning Experience building complex data sets from multiple data sources, both internally and externally Experience root causing complex and ambiguous current state outcomes and trends and tying to specific technical and nontechnical resolutions Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities Ability to educate others on statistical / machine learning methods Proficient in communicating effectively with both technical and nontechnical stakeholders. Experience with Cloud platforms such as Azure, AWS, Databricks, and AI-assisted capabilities preferred Experience with multi-echelon inventory optimization preferred Experience specific to quick service restaurant or retail inventory management beneficial, not required
Key Skills
Causal InferenceExperimentation FrameworksForecastingInventory OptimizationSupply Chain PlanningData AnalysisStatistical MethodsMachine LearningCloud PlatformsAzureAWSDatabricksAI-Assisted CapabilitiesMulti-Echelon Inventory OptimizationQuick Service Restaurant ManagementRetail Inventory Management
Categories
Data & AnalyticsRetailLogisticsManagement & Leadership
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