lead data scientist, Retail Testing Analytics (Nashville, TN)

Now Brewing – Lead Data Scientist, Retail Testing Analytics! #tobeapartner

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.

As a Lead Data Scientist on the Retail Testing Analytics team, you will lead the development of production-grade statistical frameworks, advanced analytics solutions, and optimization algorithms that power Starbucks' enterprise testing, experimentation and measurement capabilities. You will shape the future of causal measurement and experimentation by designing scalable methodologies, models, and decision-support tools tailored to Starbucks' unique business challenges.

In this role, you will partner closely with cross-functional stakeholders across Store Development, Retail Operations, Labor and Staffing, Product Innovation, Marketing, Equipment, and Technology to translate complex business questions into rigorous analytical solutions. Your work will directly inform strategic investments, operational decisions, and innovation initiatives across the enterprise.

As a Lead Data Scientist, you will...

• Design, build, and continuously enhance scalable, production-grade testing and measurement frameworks that can be applied across a wide range of business domains.
• Develop and integrate advanced statistical methodologies, causal inference techniques, optimization approaches, and machine learning models into enterprise testing-experimentation and measurement platforms.
• Lead the evaluation of strategic business initiatives by partnering with cross-functional teams to quantify business impact, identify opportunities, and support data-driven decision-making.
• Translate complex analytical findings into clear, actionable recommendations for technical and non-technical stakeholders, including senior leaders.
• Mentor and guide Data and Decision Scientists in advanced analytics, statistical methodology, experimentation design, optimization, and storytelling best practices.
• Drive technical excellence and foster a culture of innovation, continuous learning, and analytical rigor across the team.