Senior Data Scientist Lead — Production ML (Nashville)

Starbucks Corp.; Nashville (TN); On-site; USD 115,000 - 192,000; Full time

Benefits offered by this job

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

Eight paid holidays

Two personal days per year

401(k) retirement plan with employer"+

Job summary

Starbucks Corp. in Nashville, TN seeks a Senior/Lead Data Scientist to build statistical and ML solutions addressing high-impact problems and informing business decisions. You will blend hands-on model development with operational analytics for real-world workflows.

The role emphasizes cross-functional collaboration, governance, and scalable pipelines, with strong emphasis on translating complex data insights into actionable business actions.

Qualifications

• BA/BS in a quantitative field (or equivalent practical experience).
• 4+ years in data science, analytics, or a closely related field.
• Proficiency with Python or R and SQL.

Responsibilities

• Develop and apply analytical models to improve decision-making, performance, and outcomes.
• Translate business needs into data science solutions by defining the approach, sourcing data, and communicating recommendations.
• Operationalize work by building repeatable analysis and model pipelines with documentation and version control.

Skills

Analytical modeling

Data-driven decisions

Mentoring

Education

BA/BS in quantitative field

MS/PhD in quantitative discipline

Tools

Python

R

SQL

AWS

Azure

Spark

Job description

Starbucks Corp. in Nashville, TN seeks a Senior/Lead Data Scientist to build statistical and ML solutions addressing high-impact problems and informing business decisions. You will blend hands-on model development with operational analytics for real-world workflows.

The role emphasizes cross-functional collaboration, governance, and scalable pipelines, with strong emphasis on translating complex data insights into actionable business actions.