Disclaimer: This job description is for demonstration purposes only and does not represent an actual job opening.
Job Overview:
Starbucks is seeking a highly motivated and experienced part-time Data Scientist to join our Global Supply Chain team. In this role, you will be responsible for using data analysis and modeling techniques to provide insights and recommendations that drive improvements in Starbucks' supply chain operations. The ideal candidate will have a strong background in data science, excellent communication and problem-solving skills, and a passion for driving business impact.
Responsibilities:
- Work with cross-functional teams to identify opportunities for data analysis and modeling that can drive improvements in Starbucks' supply chain operations
- Develop and implement statistical models and machine learning algorithms to analyze data and generate insights and recommendations
- Collaborate with supply chain and logistics teams to identify and track key performance indicators and metrics
- Communicate findings and recommendations to stakeholders across the organization, using data visualizations and other techniques
- Continuously evaluate and improve data analysis and modeling processes and techniques
Requirements:
- Bachelor's or Master's degree in data science, statistics, computer science, or a related field
- 3+ years of experience in data science, with a focus on applying statistical and machine learning techniques to business problems
- Strong knowledge of data analysis and modeling techniques, tools, and best practices
- Excellent communication, problem-solving, and collaboration skills
- Experience with programming languages such as Python or R
- Ability to work effectively in a part-time capacity, with a flexible schedule
DemoStarbucks is an equal opportunity employer that is committed to diversity and inclusion. We welcome applications from all qualified candidates, regardless of race, color, religion, sex, national origin, age, disability, or any other legally protected status.
Disclaimer: This job description is for demonstration purposes only and does not represent an actual job opening.
