Lead Data Scientist, Retail Testing Analytics — Enterprise Impact

DataJobs; Nashville (TN); On-site; USD 146,000 - 244,000; Full time

Benefits offered by this job

401(k) retirement plan with employer (

Starbucks College Achievement Plan

Job summary

Starbucks is seeking a Lead Data Scientist for the Retail Testing Analytics team in Nashville, TN (onsite). You will design production-grade scoring frameworks, apply causal inference and ML methods, and collaborate across functions to power enterprise testing and decision-making with robust analytics.

You will mentor a team of data scientists, communicate complex results to senior leaders, and drive technical excellence in an environment that values innovation and rigorous analysis.

Qualifications

• 5+ years of progressive data science experience.
• Deep expertise in statistics, causal inference, experimental design, and advanced analytics.
• Strong software development skills with Python and SQL; experience with Databricks and Azure.

Responsibilities

• Design and enhance production-grade frameworks for testing and measurement across domains.
• Develop and integrate causal inference, optimization, and ML models into platforms.
• Evaluate initiatives by partnering with cross-functional teams to quantify impact.
• Translate analytics findings clearly to technical and non-technical stakeholders, including senior leaders.
• Mentor Data and Decision Scientists in advanced analytics, experimentation design, and storytelling.
• Foster innovation and analytical rigor within the team.

Skills

Data science experience

Communication and storytelling

Mentoring and leadership

Tools

Python

SQL

Databricks

Azure

PySpark

Job description

Starbucks is seeking a Lead Data Scientist for the Retail Testing Analytics team in Nashville, TN (onsite). You will design production-grade scoring frameworks, apply causal inference and ML methods, and collaborate across functions to power enterprise testing and decision-making with robust analytics.

You will mentor a team of data scientists, communicate complex results to senior leaders, and drive technical excellence in an environment that values innovation and rigorous analysis.