Associate Director - Data Science

What You'll Do - The leader of AI and Data Science at the enterprise level defines the organization’s overarching AI vision, manages investments, and leads cross-departmental initiatives to expand responsible AI. This role partners with executive, business, and technology leaders to transform strategic priorities into a practical AI portfolio, enterprise capabilities, and quantifiable results across revenue growth, cost savings, efficiency, customer satisfaction, and risk management. - Enterprise AI strategy and investment governance: Set the enterprise AI vision, multi-year agenda, and operating system. Formulate arguments, order high-value use cases, and supervise funding, sequencing, dependencies, delivery risk, and benefits realization. - Business value realization and executive advisory: Establish measurable outcomes and track adoption, efficiency, reliability, risk, return on investment, and business impact. Translate AI opportunities, constraints, and choices into executive-ready recommendations and implementation roadmaps. - Enterprise AI platforms and solutions: Support scalable features such as retrieval-augmented generation, AI agents, intelligent automation, document intelligence, MLOps/LLMOps, and model and agent observability. - Responsible AI and lifecycle governance: Establish policies, standards, and controls covering data privacy, security, model risk, bias minimization, regulatory alignment, monitoring, and ethical AI implementation. - Cross-functional delivery, adoption, and change: Lead multidisciplinary implementation efforts across Data Science, Analytics Engineering, AI Engineering, MLOps/LLMOps, and Agent Enablement. Encourage uptake by supporting organizational transformation and integrating solutions into business workflows. - Assemble, guide, and sustain high-performing teams. Advance enterprise AI capabilities. Handle strategic technology partnerships to drive outcomes faster while controlling costs and vendor risk. Who You Are - Degree in engineering, computer science, data science, mathematics, or a related field, or equivalent experience. - 20+ years of progressive leadership experience across Data, Analytics, Artificial Intelligence, and Digital Transformation, with significant accountability for enterprise-scale portfolios, strategic investments, and groundbreaking business outcomes. - Proven history in designing and progressing enterprise AI, Data, and Analytics strategies, transforming vision into multi-year plans, scalable operating frameworks, technological capacities, and measurable business results. - Proven ability to lead large, cross-functional teams spanning Data Science, AI Engineering, Analytics Engineering, Data Platform Engineering, MLOps/LLMOps, Product Management, and Program Delivery functions. - Extensive experience partnering with C-suite executives, senior business leaders, and technology collaborators to build strategy, prioritize investments, manage organizational change, and accelerate business outcomes. - Strong expertise in establishing and operationalizing AI governance, model lifecycle management, responsible AI frameworks, risk controls, compliance standards, security guardrails, and enterprise monitoring practices. - Experience leading and providing production-scale solutions demonstrating Machine Learning, Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), Intelligent Automation, Knowledge Systems, and Document Intelligence. - Demonstrated success leading large-scale enterprise transformation initiatives, including operating model modernization, capability development, process optimization, and technology-based business innovation. - Experience assembling and advancing high-performing teams while supporting a culture of innovation, accountability, collaboration, and continuous learning. Global Leadership & Collaborator Management - Extensive experience operating within complex Global Capability Center (GCC)