(USA) Group Director, Data Science

Job Description

Position Summary

We are seeking a high-impact, visionary leader to head our centralized eCommerce Decision Science, AI, Data Engineering, and Business Intelligence functions. This role will play a critical part in scaling our rapidly growing eCommerce business through advanced modeling, machine learning, and generative AI–driven insights.

The ideal candidate combines strategic leadership with hands-on technical depth, shaping the long-term analytics roadmap while actively improving execution and outcomes across teams. This position reports directly to the Vice President of eCommerce Decision Science & Analytics.

Key Responsibilities

Technical Leadership & Solution Development

• Lead end-to-end development of scalable data science and AI solutions.
• Oversee coding, testing, deployment, and documentation across technologies including Python, SQL, Java, and related frameworks.
• Drive proof-of-concept development and production deployment of advanced analytics systems.
• Establish engineering best practices, playbooks, and operational standards.

Problem Formulation & Business Impact

• Translate complex business challenges into data-driven solutions.
• Influence stakeholders to refine problem definitions and identify high-value opportunities.
• Design multi-stage analytical systems with measurable ROI.
• Align analytics initiatives with enterprise strategy and business priorities.

Data Strategy & Architecture

• Define enterprise data requirements, governance standards, and quality frameworks.
• Guide selection and integration of internal and external data sources.
• Lead data engineering initiatives across distributed data platforms (SQL, NoSQL, big data ecosystems).
• Unlock business value from data assets through scalable data infrastructure.

Advanced Analytics & Machine Learning

• Drive development of predictive models using advanced statistical and machine learning techniques.
• Lead experimentation frameworks, automated feature engineering, and optimization strategies.
• Explore emerging areas such as generative AI, NLP, computer vision, and optimization algorithms.
• Establish best practices for exploratory data analysis and experimentation.

Model Validation, Deployment & Scaling

• Define evaluation metrics and validation methodologies for analytical models.
• Oversee deployment of large-scale models and multi-stage ML systems.
• Optimize models for performance, scalability, and cost efficiency.
• Ensure automated testing and monitoring frameworks are implemented.

Data Visualization & Storytelling

• Establish enterprise visualization standards and tool selection.
• Translate complex analytical insights into compelling business narratives.
• Partner with UX and engineering teams to build data-driven applications.
• Present insights to executive stakeholders to influence strategic decisions.

Business Strategy & Executive Partnership

• Collaborate with senior leadership to develop business strategies.
• Evaluate investment opportunities and business cases for analytics initiatives.
• Define performance metrics and enterprise processes.
• Represent the organization externally to strengthen industry presence.

People Leadership & Culture

• Build and develop high-performing, diverse teams across data science, engineering, and BI.
• Drive talent strategy including recruitment, mentorship, and succession planning.
• Foster a culture of innovation, inclusion, and continuous learning.
• Lead with integrity, accountability, and customer-first thinking.

Minimum Qualifications

• Extensive leadership experience in Data Science, AI, or Analytics organizations.
• Strong expertise in machine learning, statistical modeling, and optimization techniques.
• Experience managing large-scale data engineering and analytics platforms.
• Proven ability to influence executive stakeholders and deliver measurable business outcomes.
• Proficiency with programming languages such as Python and SQL.
• Experience deploying production-grade ML systems.

Preferred Qualifications

• Experience in eCommerce, retail, or consumer-facing digital platforms.
• Knowledge of generative AI and emerging AI technologies.
• Track record of building enterprise data strategy across multiple domains.
• Advanced degree in Computer Science, Statistics, Mathematics, Engineering, or related field.

Compensation & Benefits

Salary ranges vary by location:

• Sunnyvale, CA: $254,000 – $481,000 annually
• Bentonville, AR: $195,000 – $370,000 annually

Additional compensation may include:

• Performance bonuses (annual or quarterly)
• Stock awards
• 401(k) with company contributions
• Comprehensive medical, dental, and vision coverage
• Paid time off, parental leave, and family care benefits
• Education benefits through Live Better U program
• Employee discounts and wellness programs