SR DIRECTOR, MACHINE LEARNING

General Summary:

This role exists to build, scale, and operationalize Dollar General’s enterprise machine learning capabilities that directly drive measurable business outcomes. The Senior Director owns the ML strategy, platforms, and teams required to move from isolated models to production-grade, governed, reusable ML systems. This leader ensures ML investments are aligned to enterprise priorities, value realization, and responsible AI standards.

Duties and Responsibilities:

• Lead enterprise machine learning strategy spanning applied ML, MLOps, experimentation, and platform capabilities aligned to business priorities.
• Build, mentor, and scale high-performing ML engineering and data science leaders across centralized and embedded delivery models
• Own end-to-end lifecycle of ML systems from problem framing and modeling through deployment, monitoring, and continuous optimization
• Partner with product, IT, security, legal, and business leaders to ensure governed, responsible, and scalable ML adoption.
• Establish standards for model evaluation, experimentation, monitoring, and value measurement tied to financial and operational impact

Knowledge, Skills and Abilities:

• Deep expertise in machine learning systems, model development, and production ML architectures
• Strong understanding of MLOps, model monitoring, experimentation, and CI/CD for ML
• Proven ability to translate business problems into scalable ML solutions with measurable impact
• Experience leading senior technical managers and principal-level engineers
• Strong judgment around responsible AI, model risk, data privacy, and governance
• Ability to influence executive stakeholders and align cross-functional teams
• Experience operating ML platforms in cloud-native environments
• Excellent communication skills bridging technical and non-technical audiences

Work Experience and/or Education:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
• Advanced degree (Master’s / MBA) in a quantitative or AI-related discipline preferred
• 10+ years of experience in machine learning, data science, or applied AI roles
• 5+ years leading ML engineering or data science teams at scale
• Demonstrated experience deploying and operating production ML systems

Experience in retail, e-commerce, supply chain, or large-scale consumer data environments preferred