Chief AI & Data Architect
Tasks
- Advise executives on AI opportunities and risks
- Coordinate regulatory alignment for AI
- Define AI and data strategy
- Define data product standards
- Define metadata semantic layers
- Define reference architectures and approved patterns
- Design target state data architecture principles
- Develop enterprise data architecture strategy
- Drive feature engineering reuse
- Ensure data governance and controls
- Ensure secure scalable auditable AI solutions
- Establish AI and analytics standards
- Establish data modeling standards
- Implement responsible AI governance
- Monitor technology and regulatory trends
- Operationalize privacy transparency explainability
- Own AI and Data Platform strategy
- Own AI and data roadmap
- Prepare executive recommendations and investment cases
- Prioritize AI data use cases
- Resolve priorities ownership funding standards conflicts
- Serve as enterprise AI and data technical authority
Perks/Benefits
Skills/Tech-stack
AI Governance | Advanced Analytics | Artificial Intelligence | Auditable systems | Cloud Platforms | Cost Optimization | Data Architecture | Data Governance | Data Modeling | Data Pipelines | Data Processing | Data Product Management | Data mesh | Data product | Embeddings | Enterprise Architecture | Explainable AI | Feature Engineering | Generative AI | Lifecycle Management | Machine Learning | Metadata Management | Model Lifecycle | Model Lifecycle Management | Privacy | Product Management | Real Time | Real-time Data | Real-time Data Processing | Scalable systems | Secure Architecture | Semantic layer | Streaming Architecture | Vector Databases
Education
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