Lead Data Scientist - Pricing, Data & Analytics

Starbucks is seeking a Lead Data Scientist for its Pricing Data Science team in Seattle, WA, working onsite. In this role, you will help shape the evolution of the pricing system by building advanced pricing models and optimization algorithms that support company-owned stores across the US and Canada.

You will lead development of a scalable, data-driven pricing framework that connects predictive analytics and optimization to business outcomes. The position also includes guiding senior and peer data scientists, partnering closely with strategy and finance, and strengthening how insights are communicated through analytics, dashboards, and decision-ready tools.

What you’ll do

• Develop a scalable pricing framework driven by data to optimize revenue outcomes.
• Integrate predictive modeling and ad hoc analyses into the pricing framework.
• Use advanced analytics to identify pricing and promotion potential.
• Apply machine learning, simulation, and scenario planning to implement optimization strategies.
• Partner with strategy and finance to align pricing tools with business goals.
• Lead data scientists and senior data scientists in advanced analytics, optimization techniques, and business impact storytelling.
• Support a culture of innovation and continuous improvement within the analytics team.

What you bring

• 5+ years of progressive experience in data science, including a proven record of end-to-end data product and model deployment with measurable business impact.
• A strong foundation in machine learning and statistical methods, including regression, classification, clustering, and causal inference.
• Advanced proficiency in Python and SQL, along with cloud-based analytics platforms such as Databricks and Azure.
• Experience creating production-grade data pipelines and model outputs.
• Strong communication and data storytelling skills, translating complex approaches into actionable insights through visualizations and dashboards using Tableau.
• Experience building in-house production systems in complex, data-rich domains.
• Mentoring experience.

Tools and technologies

• Python
• SQL
• Databricks
• Azure
• Tableau
• PySpark

Salary

USD 146,300 - 243,900 per year.

Benefits

• Medical, dental, and vision coverage
• Basic and supplemental life insurance
• 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
• Reasonable accommodations to job applicants with disabilities

Preferred skills

• Expertise in Bayesian elasticity models and causal inference.
• Experience with optimization techniques including linear programming, mixed-integer programming, or heuristic algorithms for decision support.
• Background with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments.