Director, Data Science - Stores, MCCS, Supply Chain

Macy's•Johns Creek, GA

About The Position

Macy’s is more than just a store. We’re a story. One that’s captured the hearts and minds of America for more than 160 years. A story about innovations and traditions…about inspiring stores and irresistible products…about the excitement of the Macy’s 4th of July Fireworks, and the wonder of the Thanksgiving Day Parade. We’ve been part of memorable moments and milestones for countless customers and colleagues. Those stories are part of what makes this such a special place to work. Job Overview The Director, Data Science & AI Engineering is a hands-on strategist who partners with business and technology leaders to identify, prioritize, and execute high-impact Data Science and AI opportunities. The Director drives the end-to-end lifecycle of AI and data science initiatives—from opportunity discovery, through solution design, production deployment, and ongoing optimization. By combining deep technical expertise with strong business acumen, the Director enables Macy’s to embed AI into critical workflows, unlock new sources of value, enhance customer experiences, and optimize operations in a rapidly evolving retail landscape.

Requirements

Visionary Thinking – Defines the future vision for AI engineering and ML Ops, embedding advanced models into critical workflows and scaling innovations across the organization.
Stakeholder Management – Builds strong partnerships with senior executives and business leaders, aligning AI initiatives with enterprise priorities and delivering measurable impact.
Technical Acumen – Expert in machine learning frameworks (TensorFlow, PyTorch, scikit-learn), generative AI, LLM integration, ML Ops practices, cloud platforms (GCP), containerization, CI/CD, and infrastructure-as-code.
Solution Architecture – Architects and scales ML pipelines, integrating generative AI and LLMs into production systems while ensuring reliability, scalability, and ethical deployment.
Data-Driven Decision Making – Defines success metrics, measures business impact, and translates complex data insights into actionable strategies.
Team Leadership & Talent Development – Leads, mentors, and coaches managers and individual contributors, fostering a high-performing, continuously improving Enterprise Data & Analytics team.
Cross-Functional Collaboration – Partners with Data Engineering, Architecture, Governance, and business teams to ensure alignment with data strategies, infrastructure standards, and compliance protocols.
Innovation & Continuous Learning – Stays current on emerging trends and technologies in AI, machine learning, and ML Ops to inform strategy, drive innovation, and maintain competitive advantage.
Problem Solving & Business Impact – Applies AI to solve customer and business challenges, driving growth, efficiency, and enhanced customer experiences.
Candidates with a bachelor’s degree or equivalent work experience in a related field are encouraged to apply. Advanced degree preferred.
8-10 years of experience applying data science and AI engineering in business environments, including experience leading technical teams and managing enterprise-scale initiatives.
Regularly required to sit, talk, hear; use hands/fingers to touch, handle, and feel. Occasionally required to move about the workplace and reach with hands and arms. Requires close vision.
Able to work a flexible schedule based on department and company needs.

Responsibilities

Partner with business leaders to proactively identify opportunities where AI and data science can drive growth, efficiency, and enhanced customer experiences.
Translate business objectives into actionable plans for the team, providing clear direction and prioritization to deliver strategic impact.
Serve as a trusted partner to executive stakeholders, ensuring alignment between business objectives and AI engineering strategy.
Architect, implement, and scale advanced machine learning, Agentic AI, and Generative AI solutions, managing the full lifecycle from data discovery to production deployment and ongoing support.
Ensure the accuracy, reliability, and integrity of AI solutions through rigorous validation, quality control, and adherence to ethical AI practices.
Drive performance and functionality improvements across ML pipelines, promoting automation and MLOps best practices for scalability and resilience.
Define success metrics for AI initiatives, measuring business impact and ensuring solutions deliver tangible value and ROI.
Lead, mentor, and coach managers and individual contributors, raising the talent bar across the Enterprise Data & Analytics team and fostering a culture of continuous improvement.
Collaborate cross-functionally with Data Engineering, Architecture, and Governance teams to ensure alignment with data strategies, infrastructure standards, and compliance protocols.
Guide the application of advanced AI techniques, including generative AI and large language models (LLMs), to solve business challenges and enhance customer experiences.
Present key findings and recommendations to senior leadership, influencing data-driven decision-making.
Stay current on emerging trends and technologies in AI, machine learning, and MLOps to inform team strategy and innovation.
Foster an environment of acceptance and respect that strengthens relationships, and ensures authentic connections with colleagues, customers, and communities.

Benefits

competitive pay and benefits
comprehensive health and wellness coverage
401(k) match
paid time off
eight paid holidays
continuous learning and leadership development
Merchandise discounts
Performance-based incentives
Annual merit review
Employee Assistance Program with mental health counseling and legal/financial advice
Tuition reimbursement