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VP, Data and AI

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About the position

Advance Auto Parts is seeking a visionary and strategic Vice President of Data and AI to lead the enterprise-wide data and artificial intelligence strategy. This executive will champion data as a core strategic asset, driving advanced analytics, machine learning, generative AI, and AI-powered capabilities to fuel revenue growth, optimize supply chain and inventory, enhance customer experiences across DIY and professional channels, improve merchandising decisions, and deliver operational efficiencies in a dynamic retail automotive environment. Reporting to the CTO, the VP will build and scale a high-performing Data & AI organization, foster a data-driven culture, ensure robust data governance, and partner closely with business leaders (Merchandising, Supply Chain, Stores, Digital, Marketing, Finance) to deliver measurable business impact. This position is part of a Hybrid work arrangement based at Advance Auto Parts headquarters in Raleigh, NC requiring four days/week in office.

Responsibilities

  • Strategic Leadership Define and execute the enterprise Data & AI vision and roadmap aligned with AAP's three-year financial and growth plan, focusing on AI readiness, data monetization, and competitive differentiation in the automotive aftermarket.
  • Data Platform & Governance Oversee modern data architecture (e.g., cloud-based lakehouse, ELT/ETL pipelines, master data management) to create a single source of truth for high-quality, accessible data. Champion data governance, quality, privacy, security, and compliance.
  • Advanced Analytics & AI/ML Innovation Lead development of AI/ML solutions including: Demand forecasting and inventory optimization Predictive pricing and assortment planning Personalized customer recommendations and marketing Supply chain risk prediction and logistics efficiency Generative AI for customer support, merchandising insights, and operational automation Computer vision/IoT for store and distribution center use cases
  • Business Partnership & Impact Collaborate with C-suite and functional leaders to identify high-value opportunities, prioritize initiatives, and measure ROI through KPIs (e.g., revenue lift, cost savings, customer retention, forecast accuracy).
  • Team Building & Talent Development Attract, develop, and retain top talent in data engineering, data science, AI research, and analytics. Build a culture of innovation, experimentation, and continuous learning while promoting data literacy across the organization.
  • Technology & Vendor Management Evaluate and integrate emerging tools/technologies (e.g., cloud platforms like GCP/Snowflake/Databricks/Azure, AI frameworks, GenAI models). Manage budgets, vendors, and partnerships to accelerate delivery.
  • Risk & Ethics Ensure responsible AI practices, bias mitigation, transparency, and ethical use of data/AI.

Requirements

  • Bachelor's degree required (Master's or PhD preferred) in Computer Science, Data Science, AI/ML, Statistics, Engineering, Business Analytics, or related quantitative field.
  • 12–15+ years of progressive leadership in data, analytics, AI/ML, with at least 7–10 years in senior/executive roles (e.g., VP/SVP/Head of Data & AI).
  • Proven track record in retail, e-commerce, automotive, consumer goods, or similar high-volume, data-intensive industries.
  • Experience leading large-scale data transformations, building modern data platforms, and deploying production AI/ML solutions at enterprise scale.
  • Deep knowledge of data engineering, big data technologies, cloud platforms, ML frameworks (e.g., TensorFlow, PyTorch), and GenAI applications.
  • Strong understanding of retail metrics (demand forecasting, assortment, pricing, customer lifetime value, supply chain optimization).
  • Exceptional executive presence, communication, and influence skills to engage C-suite, board, and cross-functional stakeholders.
  • Demonstrated ability to drive cultural change toward data/AI-driven decision-making.
  • Proven people leadership: building inclusive, high-performing teams.

Nice-to-haves

  • Experience in retail transformation programs (e.g., digital commerce, omnichannel, supply chain resilience).
  • Track record of delivering measurable business value (e.g., multimillion-dollar savings or revenue impact via AI/analytics).
  • Familiarity with tools like Palantir, Power BI, Databricks, Snowflake, or similar.
  • Experience with automotive aftermarket dynamics a plus.
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