MLops: • Cooperate with Google Inc to Build MLops on GCP for Customers. • Build ETL pipeline by using airflow and dataflow on GCP. • Use Kubeflow Python SDK to build training pipeline with AutoML and Custom model. • CI/CD with Cloud Repository and Cloud Build on GCP. • Continuous train pipeline build on GCP. ETL: • Batch Export Cloud SQL table to Cloud Storage by using Cloud Kubernetes Engine • Build ETL job by using Cloud Workflow on GCP NLP: • Build sentence classification model by using BERT, tf-idf, word2vec, Sentence-BERT in the government agency project. • Build Docker Image for model serving. • Use Django framework for RESTful API. Graph Data Science: • Use Graph Algorithms in Neo4j to detect smuggling crime in RFP for the government agency. • Use Neo4j to build knowledge graphs. • As an employee training speaker about teaching Neo4j Graph Database for Cathay. • Applying Data Science in Finance: Neo4j with GDS and ML for Financial Fraud Detection

• Interact with PostgreSQL • Data Wrangling • Word Tokenization • TF-IDF • Word Embedding (Word2Vec) • Topic Modelling (LDA) • Data Labeling • Assist to set up internal label system (Django)

• Quality Assurance Test • Update QA Table • Unity/Blender

• Provide foreign remittance to the client. • Help the client exchange money to foreign currency. • Process big foreign remittance data, and analyze data • Answer client all questions on foreign remittance. • Communicate and coordinate with other departments.

• Taught students to use Excel to build a stock portfolio and use big data to complete targets. • Helped the teacher teach Asset pricing. • Prepared teaching equipment for the teacher. • Offered advice for students and help them find solutions.