data scientist lead

About the Role

Key Responsibilities

• Guide the development of geospatial measurement and predictive models that inform strategic planning and investment decisions across Starbucks global store portfolio, from cannibalization to trade area scenario modeling.
• Serve as a Strategic Analytics Leader partnering closely with product and business teams to guide data-driven decisions from the corporate to neighborhood level.
• Lead the evaluation and activation of high-value global data assets (internal and external) from vehicle traffic and mobility trends to demographics, points of interest and customer data to power next-gen decision support tools.
• Apply advanced statistical and machine learning techniques (e.g., regression, causal inference, clustering) to solve complex, ambiguous store portfolio challenges.
• Translate insights into action through advanced statistical and data visualization techniques, delivering clear, impactful store growth recommendations that guide strategic decision-making.

Requirements

• 5+ years of progressive experience in decision or data science, with a proven track record of end-to-end data product and model deployment that delivers measurable business impact.
• Demonstrated ability to advance geospatial analytics in applied settings across industries such as retail, real estate, energy, utilities, telecom, logistics, and consumer tech.
• Strong foundation in machine learning and statistical techniques, including regression, classification, clustering, and causal inference.
• Advanced proficiency in Python, SQL, and cloud-based analytics platforms (e.g., Databricks, Azure), with experience developing production-grade data pipelines and model outputs.
• Excellent communication and data storytelling skills, with the ability to translate complex methodologies into clear, actionable insights through compelling visualizations and dashboards using tools like Tableau.
• Proven ability to work effectively across cultural and language barriers in global, cross-functional environments.
• Experience building internal decision support in complex and data-rich domains.

Nice to Have

• Experience with geospatial analytics in applied settings across various industries.
• Experience working with vehicle traffic, mobility trends, demographics, and points of interest data.

Qualifications

• Educational background or certifications are not explicitly specified, but extensive experience in data science and geospatial analytics is required.

Benefits & Perks

• Access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits.
• Short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation, sick time, paid holidays, and personal days.
• Participation in a 401(k) retirement plan with employer match, discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), and incentivized emergency savings.
• Financial well-being tools, tuition coverage for a first-time bachelor’s degree through ASU’s online program, student loan management resources, and other educational opportunities.
• Access to backup care and DACA reimbursement.