Ross Davis is the Asia Pacific lead for IBM’s Data & AI Expert Labs practice. In this role, Ross provides technical leadership and direction to information governance, architecture and Artificial Intelligence initiatives across the region.He leads technical and business thinking for Master Data Management and Data Governance where for operational (real-time API) service integration is required. He also designs Artificial Intelligence (Aiops) pipelines, real-time image classification, embedding of LLM/MMM services into model IDE’s and integration of Predictive risk-scoring with operational rules-enginesRecent experiences include:- Enterprise Architect, Regional MDM Implementation, Tier 1 Bank, Australia & New Zealand- Analytics, LLM and Data Governance, Australian Govt- Data Governance and Operational Model Consultant, Tier 1 Bank, SE Asia- Data Science Mental Health prediction, Australian Govt- Tensorflow real-time image recognition, Australian Govt- Enterprise Architect, Regional MDM implementation, Tier 1 Bank, SE Asia- Enterprise Architect, Global MDM implementation, Tier 1 Bank, SE Asia- Cloud Architect, Global Mining machine learning and Data Science implementation, Australia & US- Material & Logistics Master Data Architect, Australian Defence- Data Governance Consultant, Regional MDM implementation, Insurance & Wealth, SE Asia- Enterprise Architect, Regional MDM implementation, Tier 1 Bank, CGC- Cloud Architect, l MDM implementation, Tier 2 Bank, Australia- MDM Architect, National Health Ministry, New Zealand- Data Governance Consultant, cross-Govt, SE AsiaRoss has either managed, architected or advised over 30 CDO and CDAO governance initiatives in Government, Retail Banking, Institutional Finance, Insurance, and Manufacturing. This has included executive coaching of CDO’s/CAO’s with building operating models implementations of AI and Enterprise Data GovernanceRoss is also an IBM Patent holder for Image acquisition and parsing, with high-velocity frame-detection and intelligent object binning. He has architected a number of AWS, Azure and Hybrid Cloud patterns for API’s that automate the flow outputs from Machine Learning into low-latency rules execution