Data Scientist

Starbucks; Nashville (TN); On-site; USD 99,000 - 150,000; Full time

Benefits offered by this job

Health coverage

Life insurance

Disability coverage

Parental leave

Tuition coverage

Job summary

Starbucks in Nashville, TN is seeking a Data Scientist to turn data into decision-ready insights. You will extract, clean, and shape data, build core models and pipelines, and deliver analyses that influence business decisions.

The role emphasizes collaboration, clear communication of methodologies, and the ability to present findings through dashboards using SQL, Python/R, Tableau or Power BI.

Qualifications

• Bachelor’s degree or equivalent blend of education and work experience.
• 1+ year hands-on data science, analytics, or related field.
• Strong SQL and Python and/or R for data prep, pipelines, and modeling.
• Familiarity with regression, classification, decision trees, clustering, and causal inference.

Responsibilities

• Collect, transform, and validate data to create analysis-ready datasets and structures for measurement.
• Develop and refine data science models and pipelines, building workflows for training and delivery.
• Present findings clearly with dashboards/visualizations and translate outcomes into actionable insights.

Skills

SQL

Python

R

Tableau

Power BI

Communication

Education

Bachelor's degree (BA/BS)

MS/PhD (preferred)

Tools

Tableau

Power BI

Job description

This onsite Data Scientist role is based in Nashville, TN, with responsibilities centered on extracting and shaping data, building core data science models and pipelines, and delivering decision-ready insights to inform business decisions. Salary range: USD 99,900 - 150,000 per year.

Responsibilities

• Collect, transform, and validate data using SQL and other suitable frameworks to produce analysis-ready datasets and supporting dimensional or relational structures for measurement and decision making.
• Develop and refine core data science models and their pipelines, creating data workflows for training and delivering model outputs within collaborative codebases.
• Present findings clearly by outlining methodological choices, constructing dashboards and visualizations to validate results and monitor model performance, and translating outcomes into actionable implications.

Requirements

• At least one year of hands‑on experience in data science, applied analytics, or a related field.
• Bachelor's degree (BA/BS) or an equivalent blend of education and work experience.
• Strong skills in SQL and Python and/or R for data preparation, pipelines, and modeling.
• Familiarity with standard modeling approaches such as regression, classification, decision trees, clustering, and causal inference.
• Experience using data visualization tools like Tableau, Power BI, or equivalent.
• Strong communication abilities and meticulous attention to detail.

Technologies

• SQL
• Python
• R
• Tableau
• Power BI

Benefits

• Health coverage including medical, dental, and vision benefits
• Basic and supplemental life insurance
• Additional voluntary insurance options
• Short‑term and long‑term disability coverage
• Paid parental leave
• Reimbursement for family expansion costs
• Vacation accrues from the start of employment
• Sick time accrual at 1 hour per 25 hours worked
• Eight paid holidays
• Two personal days annually
• 401(k) retirement plan with employer matching contributions
• Discounted company stock through the Equity Incentive Program and Starbucks equity program Bean Stock
• Emergency savings incentives
• Financial well‑being tools
• Full tuition coverage for a first bachelor's degree via ASU Online through the Starbucks College Achievement Plan
• Student loan management resources
• Backup care options
• DACA reimbursement

Preferred Qualifications

• A degree in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, Economics, Psychology, or related disciplines
• MS or PhD is preferred
• Experience working in shared analytics or engineering environments with version control, documentation, and reproducible workflows
• Experience supporting model measurement and monitoring through dashboards and performance reporting