Senior/Lead Data Scientist, Data & Analytics
Job Description
Starbucks is seeking a Senior/Lead Data Scientist, Data & Analytics to develop analytical models and machine learning solutions that guide business decisions and operationalize insights across cross-functional teams. This onsite role is based in Seattle, WA.
Role Details
Location: Seattle, WA (onsite)
Salary: USD 130,300 - 217,400 per year
Minimum Experience: 4 years
Education: BA/BS in a quantitative field
Responsibilities
- Create and apply analytical models using statistical methods or machine learning to enhance decision making, performance, and customer and partner outcomes.
- Translate business challenges into data science solutions by outlining approach, identifying and validating data sources, and delivering clear recommendations to both technical and non-technical stakeholders.
- Operationalize work through repeatable analysis and model pipelines, monitor and improve model performance over time, and contribute to shared standards including documentation, version control, and reproducibility.
Requirements
- At least four years of experience in data science, applied analytics, or a closely related field
- Bachelor's degree in a quantitative field or equivalent practical experience
- Proficiency in Python or R and SQL
Technologies
- Python
- R
- SQL
- AWS
- Azure
- Spark
Benefits
- Medical, dental, and vision insurance, plus basic and supplemental life insurance
- Short-term and long-term disability coverage
- Paid parental leave
- Family expansion reimbursement
- Paid vacation from date of hire
- Sick time accrued at 1 hour per 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 and financial well-being tools
- 100 percent 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 additional educational opportunities
- Backup care
- DACA reimbursement
Preferred Qualifications
- Master’s or PhD in a quantitative discipline or equivalent advanced experience
- Experience deploying or maintaining models in production environments, including monitoring, retraining, and performance measurement
- Experience with cloud analytics platforms (AWS or Azure) and distributed computing (Spark)
- Familiarity with experimental design or causal inference and translating results into business actions
- Proven ability to mentor others and influence cross-functional partners toward adoption