Experienced Full Stack Data Scientist – Web & Cloud Application Development for Global Retail Leader
About Us
At Starbucks, we're on a mission to inspire and nurture the human spirit – one person, one cup, and one neighborhood at a time. We're known for creating exceptional leaders who share our passion for innovation, customer experience, and community engagement. As a global leader in the retail industry, we're committed to fostering a diverse and inclusive work environment that celebrates individuality and promotes growth opportunities for all.
Job Summary
We're seeking an experienced Full Stack Data Scientist to join our Information, Research, Insights, and Business Operations team. As a key member of our cross-functional team, you'll work closely with data engineers, data researchers, business analysts, and external partners to drive business decisions using data and analytics. Your expertise in determining, automating ETL processes, and building predictive models using structured or unstructured data will help us unlock new insights and drive business growth.
Key Responsibilities
- Extract data from various data sets; perform exploratory data analysis, clean, massage, and aggregate data to support business decisions.
- Determine the most effective analysis approach to address business challenges; integrate AI algorithms where applicable.
- Utilize scaling and automation to improve data processing methods and reduce manual effort.
- Transform model results into actionable insights for end-users through visualizations, clear tables, and engaging presentations.
- Collaborate with technical and non-technical stakeholders to understand their needs and provide guidance on data analysis and interpretation.
Essential Qualifications
We're looking for a highly motivated and experienced data scientist with a strong foundation in quantitative disciplines, including:
- Bachelor's degree in a quantitative field (e.g., Data Science, Mathematics, Computer Science, Engineering, Economics, Quantitative Sociology, or a related field).
- At least 2+ years of industry experience in data science, with a proven track record of delivering high-impact projects.
- Strong foundation in predictive and statistical modeling, AI, and machine learning, with expertise in all stages of the modeling pipeline.
- Experience building complex data sets from various data sources, both internal and external.
- Strong SQL, database, and ETL skills, including data cleaning and management.
- High-level proficiency in Python, R, or other programming languages.
- Ability to apply data insights to multidisciplinary business standards and practices to achieve successful outcomes in cross-functional projects and initiatives.
- Excellent communication and interpersonal skills, with the ability to work with both technical and non-technical stakeholders.
Preferred Qualifications
We're looking for candidates with the following preferred qualifications:
- Experience working with cloud platforms like Azure, AWS, or Google Cloud.
- Knowledge of data visualization tools and techniques.
- Experience with agile development methodologies and version control systems.
- Strong problem-solving skills and ability to work in a fast-paced environment.
Career Growth Opportunities and Learning Benefits
We're committed to helping our employees grow and develop their careers. As a data scientist at Starbucks, you'll have access to:
- Regular training and development programs to enhance your skills and knowledge.
- Opportunities to work on high-impact projects and collaborate with cross-functional teams.
- A dynamic and inclusive work environment that fosters creativity, innovation, and experimentation.
- A competitive salary and benefits package, including health insurance, retirement plans, and paid time off.
Work Environment and Company Culture
We're proud of our company culture, which values diversity, equity, and inclusion. As a data scientist at Starbucks, you'll be part of a team that's passionate about making a positive impact on our customers, communities, and the environment. Our work environment is collaborative, dynamic, and fast-paced, with a focus on innovation, creativity, and continuous learning.