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Decision Scientist - Staffing, Reporting And Data Analytics
Company | Starbucks |
Address | Seattle, WA, United States |
Employment type | FULL_TIME |
Salary | |
Category | Food and Beverage Services,Manufacturing,Retail |
Expires | 2023-09-28 |
Posted at | 8 months ago |
Now Brewing – Decision Scientist – Staffing, Reporting, & Data Analytics! #tobeapartner
- Effectively present complex technical material to non-technical audiences in an approachable way. Provide analytic support (code documentation, data transformations, algorithms, etc.) to implement rules and model insights / recommendations into business processes.
- Use your working knowledge and understanding of Starbucks business, and business acumen in general, to collaborate with colleagues at all organizational levels, including both retail operations / operations services, finance, and Starbucks Technology.
- Execute extraction and synthesis of data from various databases, including Azure: data lake storage, SQL server and legacy systems: Oracle; perform exploratory data analysis, cleanse, massage, and aggregate data. Can handle and maintain the confidentiality of highly sensitive information required for statistical analysis and modeling techniques, including descriptive and predictive analysis (e.g., regression analysis, clustering, anomaly detection).
- Business experience with several data visualization tools (e.g., Tableau, Power BI)
- Proficiency with SQL and Python; familiarity with both preferred
- Demonstrated experience with Microsoft Office, including PowerPoint
- Staffing or Workforce Analytics preferred.
- Working knowledge of statistics (descriptive, regression, etc.)
- Education: BA/BS with preferred concentration discipline in Stats, Math, Comp Sci, Engineering, Econ, Psychology, Quantitative Social Science or similar
- Skills: Ability to handle and maintain the confidentiality of highly sensitive information
- Years of experience in specific field or utilizing designated skills: Minimum 1 years’ Experience
- Familiarity with database design and/or data engineering preferred
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