From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
This is a team where technology, analytics, and strategy converge to deliver impact at scale.
This role sits at the core of our Data & Analytics organization, a team dedicated to transforming how data empowers decision-making across the company. Our mission is to democratize data— as a product to enable cross-functional teams and leaders to make confident, data-driven decisions that impact more than 18,000 coffeehouse leaders.
The work is split into two key areas:
- Focused on decision science & data democratization &, creating accessible, reliable, and actionable insights (50%)
- Driving innovation through AI and BI trends, accelerating our journey toward data modernization (50%)
Who you are…
- A natural problem solver who thrives on tackling complex challenges and finding innovative solutions.
- Product-minded with an analytical lens, always thinking about how data can be shaped into impactful products that drive business outcomes.
- Passionate about data—not just for its technical depth, but for the difference it can make in the lives of those who consume it, creating measurable value at scale.
- Self-motivated and proactive, with the ability to navigate ambiguity and deliver results in a fast-paced, evolving environment.
As a sr decision scientist, you will…
In this role, you will act as a product owner and thought leader, blending the worlds of decision science and AI enablement to deliver innovative, scalable solutions that empower data-driven decisions across the enterprise.
Data & Decision Science (50%)
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Analyze data to deliver actionable insights for supply growth and program design (SQL, Power BI, Tableau, (Micro)Strategy).
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Perform quantitative analyses to seize opportunities and build investment cases for new initiatives (Python, R, ML & Statical Modeling)
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Establish reporting cadence, monitor key metrics, and share regular updates with stakeholders (Dashboarding, KPI Tracking, Data Visualization).
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Provide ad hoc analytical support for initiatives in Marketing, Supply Chain, and Coffeehouse Operations (Data Wrangling, Business Analysis).
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Coach and mentor other Decision Scientists within the team to strengthen analytical capabilities, promote best practices, and foster a culture of continuous learning.
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Partner with cross-functional teams (Operations, Advanced Analytics, Data Science, Product) to align strategies (Collaboration Tools: Jira, Confluence, Teams). AI Enablement & Platform Development (50%)
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Stay ahead of emerging AI/BI trends to accelerate data modernization efforts (Generative AI, Augmented Analytics).
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Identify and prioritize AI and BI opportunities with clear value hypotheses and success metrics (AI/ML Concepts, Business Case Development).
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Proficiency in Python, SQL, and agentic coding tools such as GitHub Copilot or similar (Claude Code, Cline, Codex, Gemini).
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Collaborate with architects and product owners to enable AI-driven insights and modern BI capabilities (Cloud Platforms: Azure, APIs).
We’d love to hear from people with…
- Minimum 5+ Years Experience
- Education: BA/BS w/ concentration in business or quantitative discipline - Stats, Math, Comp Sci, Engineering, Econ, or similar; Masters preferred
- Ability to balance a detail-oriented, hands-on approach with creative, “outside-the-box” thinking.
- Strong communication and collaboration skills with cross-functional partners, including those with and without technical backgrounds.
- Demonstrated willingness to learn continuously, adopt new technologies and approaches, and share knowledge within the technical community.
- Growth-minded, solution-oriented approach with a proven track record of driving projects from concept to impact.
Preferred Qualifications
- Prior experience integrating AI-driven insights into dashboards, semantic models, citizen development, or data marts in collaboration with BI engineering, is plus advantage
- Technical expertise in advanced AI techniques and building AI-orchestrated pipelines for complex data analysis