Find & Apply For Analytics Manager Jobs in Hartsville, Tennessee

Senior Manager, Data Science Date Posted:

29 August 2026

Closing Date:

September 28, 2026

Recruiter:

Starbucks Location:

Hartsville, Tennessee Salary:

USD155,000

to

USD210,000

Job Type & Industry:

Data Science, Scientific & Research Contract Type:

Permanent Job Reference:

2944532318-2 Apply for this job now Job Description Starbucks is seeking a Senior Manager, Data Science to lead advanced analytics that power decisions across our global coffee and food business. In this role, you'll build and guide a high-performing data science team to optimize store operations, personalize customer experiences, and improve supply chain and pricing strategies. You will design and deploy machine learning models, collaborate with cross-functional partners, and translate complex insights into clear, actionable recommendations. You'll champion data best practices, mentor partners, and support Starbucks' commitments to ethical sourcing, sustainability, and an inclusive, values-driven culture. Responsibilities Lead and mentor a data science team, setting strategy, priorities, and best practices. Design, build, and deploy machine learning and statistical models to support key business decisions. Partner with operations, marketing, digital, and supply chain teams to define analytics use cases and deliver actionable insights. Translate complex analytical findings into clear recommendations for senior leadership. Establish standards for data quality, model governance, and experimentation across the organization. Develop experimentation frameworks (A/B tests) to measure impact of new initiatives. Collaborate with data engineering to ensure robust data pipelines and scalable model deployment. Monitor model performance and refine solutions based on business outcomes and new data. Influence long-term data and analytics roadmap in alignment with Starbucks' mission and values. Foster an inclusive, learning-focused culture within the data science team. Required Skills Machine learning Statistical modeling Python RSQLData visualization (e.g., Tableau, Power BI) Big data platforms (e.g., Spark, Hadoop) A/B testing and experimentation Cloud analytics (e.g., AWS, GCP, Azure) Leadership and team management