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# Lead Data Scientist

- **Company:** Starbucks
- **Location:** Madison, WI, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Configuration Management, Computer Networks, Distributed Systems, R (Programming Language), Python (Programming Language), Machine Learning, SQL Databases, Scripting, Apache Spark, Software Version Control
- **Published:** August 30, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-lead-data-scientist-data-analytics-nashville-tn-madison-tn--84fe8697-555a-4fcc-ae79-d66fb7ff7dee

## About the Role

* 4+ years in data science, applied analytics, or a closely related field
 * BA/BS in a quantitative field (or equivalent practical experience)
 * Proficiency with Python or R and SQL

Preferred qualifications:

 * MS/PhD in a quantitative discipline (or equivalent advanced experience)
 * Experience deploying or maintaining models in production environments (monitoring, retraining, performance measurement)
 * Experience with cloud analytics platforms (e.g., AWS or Azure) and/or distributed computing (e.g., Spark)
 * Familiarity with experiment design / causal inference and translating results into business actions
 * Demonstrated ability to mentor others and influence cross-functional partners toward adoption, Amazon Web Services (AWS), Analysis Skills, Brewing, Cloud Computing, Collective Bargaining, Communication Skills, Computer Networks, Cross-Functional, Data Analysis, Data Quality, Data Science, Distributed Computing, Documentation, Environmental Monitoring, Experiment Design, Healthcare Reimbursement, Machine Learning, Mentoring, Microsoft Windows Azure, Performance Management, Performance Metrics, Performance Modeling, Production Systems, Python Programming/Scripting Language, R Programming Language, SQL (Structured Query Language), Source Code/Configuration Management (SCM), State Ordinances, Statistical Modeling, Statistics, Student Loans, Tuition Fees

## Description

* Develop and apply analytical models (statistical and/or machine learning) to improve decision-making, performance, and customer/partner outcomes.
 * Translate business problems into data science solutions by defining approach, sourcing/validating data, and communicating clear recommendations to technical and non-technical stakeholders.
 * Operationalize your work by creating repeatable analysis/model pipelines, improving model performance over time, and contributing to shared standards (documentation, version control, reproducibility).


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