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上海市, 中国
Hybrid
The Role
Reporting directly to VP, Technology GC, the Senior Director, Enterprise Data & AI (ED&AI) GC is a senior leadership role responsible for shaping and executing the enterprise data, analytics, and AI vision across Greater China. This leader will build and scale team to power data-driven decision making, automation, and breakthrough AI-enabled products that support GC's business growth.
In this role, you will:
Define and articulate a compelling enterprise data & AI vision, strategy, and multi-year roadmap in alignment with GC business priorities and our global technology strategy.
Lead and grow teams to build a high-performing and integrated organization.
Partner with the Global and Geography Technology teams to deliver scalable, 'bleeding edge' technology solutions that push the boundaries of what the business can do today and accelerate change in GC.
Evangelize data, analytics, and AI capabilities across the business to drive adoption of data-driven decision making, automation, and AI-powered ways of working.
Drive measurable business outcomes through data, analytics, and AI, accelerating consumer engagement, digital commerce growth, speed of decision-making, and operational efficiency across Greater China.
Lead the annual process of creating, maintaining, and implementing the GC ED & AI Technology Portfolio.
Identify and prioritize high-impact opportunities to leverage AI/ML and analytics to address customer needs and solve complex, high-business-impact problems.
Oversee end-to-end delivery of data platforms and AI/ML products, from ideation and architecture through launch, iteration, and operations.
Elevate engineering excellence through best practices in data architecture, MLOps, security, scalability, uptime, and reliability.
Ensure adherence to data governance, AI ethics, privacy, and regulatory standards in partnership with legal and compliance teams.
Manage cross-functional teams and stakeholders — including product owners, data engineers, ML engineers, and scrum masters — to deliver against a shared backlog.
What You'll Need to Succeed
Experience & Leadership
15+ years in data and analytics engineering, data science, AI/ML, or data product roles, with a proven track record of building and scaling enterprise data & AI capabilities.
Significant experience leading and growing multi-disciplinary technology teams, including people leaders, and providing technical leadership to cross-functional and business teams.
Demonstrated success delivering AI/ML-powered products and enterprise-scale data platforms from strategy through production.
Experience leading AI transformation beyond data science initiatives and agentic workflows to also include leading AI-driven operating model transformation with AIDLC (AI Development Life Cycle).
Technical Expertise
Data or analytics engineering experience with 'big data' technologies and platforms (e.g., Hadoop ecosystem, Spark, Hive).
Knowledge of and experience with cloud technologies (e.g., AWS – EMR, S3, Lambda) and migration of tools/platforms from on-prem to the cloud.
Strong understanding of AI/ML technologies, data pipelines, machine learning frameworks, and modern cloud infrastructure.
Experience with data warehousing, dimensional modeling, ETL development, streaming/event processing (e.g., Kafka, Kinesis), and data visualization/BI tools.
Familiarity with Agile/Scrum product development methodologies and MLOps/DevOps practices.
Leadership & Soft Skills
Exceptional strategic thinking, problem-solving, and the ability to translate business needs into a data & AI roadmap.
Excellent communication and stakeholder-influencing skills, including with senior/executive leadership.
Ability to thrive and lead in a fast-paced, ambiguous, and rapidly evolving environment.
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field; MBA a plus.
Experience with AI ethics, privacy, and regulatory considerations, particularly within Greater China.
Knowledge of industry-specific AI applications (e.g., retail, e-commerce, supply chain, etc.).
Experience partnering across global and geography technology organizations in a matrixed environment.
