Catherine Wang

Acted as APAC's technical authority for Generative AI, advising strategic customers and internal teams on complex GenAI challenges and solutions. Partnering with senior customer leaders to establish GenAI strategies, identify high-value applications, bring concepts to product launch and bring customer feedback to qualified backlogs supporting AI roadmaps at Google Cloud. Drove customer time-to-value through strategic guidance and hands-on prototype development. Responsibilities - Led technical engagements for major strategic customers in APAC, serving as their trusted technical thought partner to ideate and build novel applications using GenAI. - Designed and implemented solution-based sales plays tailored to APAC market trends and customer needs. - Provided technical enablement and mentorship to enhance google technical field team skills and foster collaboration. - Represented Google Cloud at industry events, building brand visibility and thought leadership

I lead the conversation of AI / ML strategy and implementation with our customer. Specializing in * Large Language Models, Generative AI * Enterprise scale MLOps * Personalization and Recommendations * Responsible AI, Explainable AI

- Delivery industry leading servce offering in Large Language Models - Leading the consultancy and assisting in engineering the enterprise scale AI and ML solutions

- Enterprise Cloud Adoption and Strategy - Enterprise Well Architect best practices - Unified Cloud Data Platform, modern data warehousing, Lakehouse, Data Mesh, Data fabric. - Data Governance, Compliance and Security - Building central of excellent for Data Science, and Advanced Analytics team. Designing and implementing pipelines and workflows automation, infrastructure abstraction. - MLOps, DataOps, and DevOps Best Practices - Distributed AI and Lightweight Model deployment

KPMG's new horizon of corporate-funded venture in ISV (Innovation, Solution, and Venture). The group represents the collective thinking of KPMG leadership into the future business, its people and the effort to nurturing the innovation. - Big data and Cloud Architect - Machine Learning Engineer / MLOps - AI Strategy, Data Science - Edge computing - NLP, Deep learning, Chatbot

• Led reporting and analysis related initiatives for payment and booking system. • Customer segmentation, campaign strategies, propensity model to track lapsing customers and predict customer churn. Discovery customer life time value. • Deploy online learning model for health program recommendation system, introducing bundle deal to improve corss&up sell. • Extracting, learning and aggregating data, using Python and R to create descriptive/inferential statistical reports. pitching ideas and insight to stakeholder

• email marketing, eCommerce website development, manage social media channel, SEO, SEM, etc. • Using advertising activities data – click – through rates, conversion rates, cost-per-click, and cost per acquisition – to conduct analysis and direct marketing campaigns.

XCS224N - Natural Language Processing with Deep Learning XCS224U - Natural Language Understanding XCS229 - Machine Learning Strategy and Reinforcement Learning

Mathematics and Probability Statistical Modeling and Computation in Application Probabilistic Graphical Models Machine Learning and Deep Learning