Lead Data Scientist, Retail Testing Analytics
Manager
Artificial Intelligence
Big Data
Bigdata
Cloud Data Engineering
Cloud Data Platform
Cloud Operations
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Data
Data Analysis
Data Analytics
Data Engineer
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Data Lakehouse
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Machine Learning Engineer
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Spark
SQL
Job Description
Starbucks is seeking a Lead Data Scientist for the Retail Testing Analytics team in Nashville, TN (onsite). In this role, you will help power enterprise testing, experimentation, and measurement with production-grade statistical frameworks, advanced analytics solutions, and optimization algorithms. You will partner across functions to turn business questions into causal measurement and experimentation capabilities, along with decision-support tools that help leaders make confident, data-driven choices.
What you’ll do
- Design and enhance scalable, production-grade frameworks for testing and measurement that can be applied across multiple business domains.
- Develop and integrate advanced methods including causal inference techniques, optimization approaches, and machine learning models into enterprise testing, experimentation, and measurement platforms.
- Evaluate strategic initiatives by partnering with cross-functional teams to quantify business impact, identify opportunities, and enable data-driven decision-making.
- Translate analytics into action by communicating complex findings clearly to technical and non-technical stakeholders, including senior leaders.
- Mentor and elevate the team by guiding Data and Decision Scientists in advanced analytics, experimentation design, statistical methodology, optimization, and storytelling best practices.
- Drive technical excellence by fostering a culture of innovation, continuous learning, and analytical rigor.
What you bring
- 5+ years of progressive data science experience, including a track record of developing and deploying end-to-end analytical products, statistical models, or data science solutions with measurable business impact.
- Deep expertise in statistics, causal inference, experimental design, and advanced analytics, including the ability to apply machine learning and optimization to solve complex problems.
- Strong software development skills with advanced proficiency in Python and SQL, plus experience with cloud-based analytics platforms such as Databricks and Azure, including production-grade analytical solutions and data pipelines.
- Experience operationalizing platforms for experimentation, testing, measurement, and causal inference.
- Exceptional communication and data storytelling through presentations, visualizations, dashboards, and written documentation that translate sophisticated concepts into actionable recommendations.
- Experience building enterprise-scale systems in complex, data-rich environments while balancing methodological rigor with practical business needs.
- Leadership and mentoring experience with a strong interest in developing talent and raising the team’s technical capabilities.
- Proven collaboration with business leaders and cross-functional stakeholders to influence strategy and drive measurable outcomes.
- Experience with PySpark and Databricks for distributed computing and large-scale data processing.
Tools you’ll work with
Python, SQL, Databricks, Azure, PySpark
Compensation and benefits
Salary: USD 146,400 - 243,900 per year.
- Medical, dental, and vision
- Basic and supplemental life insurance
- Other voluntary insurance benefits
- Short-term and long-term disability
- Paid parental leave
- Family expansion reimbursement
- Paid vacation from date of hire
- Sick time (accrued at 1 hour for every 25 hours worked)
- Eight paid holidays
- Two personal days per year
- 401(k) retirement plan with employer match
- Discounted company stock program (S.I.P.)
- Starbucks equity program (Bean Stock)
- Incentivized emergency savings
- Financial well-being tools
- 100% upfront tuition coverage for a first-time bachelor’s degree through Arizona State University’s online program via the Starbucks College Achievement Plan
- Student loan management resources
- Access to other educational opportunities
- Backup care
- DACA reimbursement