Data Scientist

Starbucks is seeking a Data Scientist in Seattle, onsite, to partner with cross-functional teams, unravel complex data relationships, and build core data science models that inform business decisions.

Responsibilities

• Extract, transform, and validate data using SQL and other appropriate tools to produce analysis-ready datasets and scalable dimensional/relational processes that support measurement and decision making.
• Develop or refine data science models and associated pipelines, creating data workflows for model training and outputs within shared codebases.
• Communicate insights clearly by detailing methodology, building dashboards and visualizations to validate results and monitor model performance, and translating outputs into actionable recommendations.

Requirements

• 1+ year of experience in data science, applied analytics, or related roles
• BA/BS or equivalent experience
• Proficiency in SQL and Python and/or R for data preparation, pipelines, and modeling
• Working knowledge of common modeling techniques such as regression, classification, decision trees, clustering, and causal inference
• Experience with data visualization tools (Tableau, Power BI, or similar)
• Strong communication skills and meticulous attention to detail

Technologies

• SQL
• Python
• R
• Tableau
• Power BI

Benefits

• Medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits
• 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
• 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

Preferred Qualifications

• Degree concentration in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, Economics, Psychology, Quantitative Social Science, or related
• MS or PhD advanced degree preferred
• Experience in shared analytics/engineering environments with version control, documentation, and reproducible workflows
• Experience supporting model measurement and monitoring through dashboards and performance reporting
• Expertise in building Bayesian elasticity models and causal inference
• Experience in optimization techniques such as linear programming, mixed-integer programming, or heuristic algorithms for decision support