diff --git a/_data/cv.yml b/_data/cv.yml index 07167c3bef95b..73425a00bd8ac 100644 --- a/_data/cv.yml +++ b/_data/cv.yml @@ -4,11 +4,11 @@ - name: "Name:" value: Gary Goh Shing Wee - name: "Experience:" - value: "3 years academic experience in machine learning and predictive modeling + 1 year industrial experience in building a complex recommendation system for an online video live-streaming and community platform" + value: "8+ years across GenAI, machine learning, and data platform engineering — spanning the full data function: data engineering, analytics, data science, and MLOps deployment" - name: "Interest:" - value: Data-driven Artificial Intelligence applications + value: Data-driven and agentic AI applications; data & AI governance - name: "Proficiency:" - value: Large-scale data processing using Hadoop and Spark SQL and training deep neural networks with deep learning frameworks such as TensorFlow and PyTorch + value: Architecting governed data warehouses on Databricks with CDC streaming via AWS DMS, and shipping LLM / agentic systems to production (built with TensorFlow and PyTorch) - name: " :" value: garygsw@gmail.com - name: " :" @@ -17,6 +17,19 @@ - title: Work Experience type: table contents: + - title: Data Scientist + subtitle: "WhiteCoat — SEA digital health platform (SG/MY/PH/HK/ID)" + year: 2024-Present + start_date: May 2024 + end_date: Present + location: Singapore + description: + - Work across the full data function end to end — data engineering, analytics, data science, and AI transformation — supporting management decision-making and fundraising + - Architected Data Warehouse 2.0 on Databricks, migrating to a governed native catalog with CDC streaming via AWS DMS and cutting data-platform costs by ~80% + - Designed a company-wide AI operating model — a git-based knowledge base plus a governed MCP layer connecting AI agents to live company data (Databricks, Jira, GitHub, Drive, Gmail, Mixpanel) — and rolled out Claude and GPT/Codex org-wide with read-only and PII-ringfencing guardrails + - Built a self-healing LLM pipeline that auto-classifies Databricks job failures, self-repairs or opens PRs, and closes Jira tickets, eliminating manual triage + - Deployed predictive models, including quantile-regression doctor-demand forecasting, an AI Fraud/Waste/Abuse detection engine across 14 risk categories, and B2B corporate segmentation + - Data lead for the Series C fundraise data room; delivered self-serve natural-language analytics via Databricks Genie and an MCP-connected agent - title: Data Scientist subtitle: "Sea Ltd — Garena" year: 2021-2022 @@ -97,20 +110,24 @@ contents: - name: " GitHub:" value: "https://github.com/garygsw" + - name: "GenAI / ML:" + value: LangChain, LangGraph, MCP, RAG, agents, Claude Code, TensorFlow, PyTorch, scikit-learn, MLflow + - name: "Data & Platform:" + value: Databricks, Apache Spark/Hive/Hadoop, AWS DMS (CDC), Unity Catalog, ETL pipeline design + - name: "Governance:" + value: AI & data governance, Unity Catalog access control, PII ringfencing, read-only guardrails - name: "Programming languages:" - value: Python, C/C++/C#, Javascript, Java, Microsoft VBA, R - - name: "Operating systems:" - value: Mac OS, Windows, Ubuntu, Raspberry Pi OS, Linux Mint + value: Python, SQL, Bash, Javascript, C/C++/C#, R, VBA + - name: "Cloud:" + value: AWS (S3, EC2, Lambda, SageMaker, Bedrock, AgentCore), GCP (GCS, Vertex AI) - name: "Python libraries:" - value: PyTorch, NumPy, Pandas, SciPy, Keras, Theano, scikit-learn, SpaCy, Django, ... - - name: "Frameworks:" - value: Jupyter, Qt, AWS, Miscrosoft .NET 4.5, Cordova + value: PyTorch, NumPy, Pandas, SciPy, Keras, scikit-learn, SpaCy, Django, ... - name: "Database systems:" - value: MySQL, PostgreSQL, SQLite, MongoDB - - name: "Client-side technologies:" - value: HTML5, CSS3, JQuery, D3.js, AngularJS - - name: "Other software:" - value: Automod, AIMMS, Adobe Photoshop and Illustrator + value: MySQL, PostgreSQL, MSSQL, MongoDB, Databricks + - name: "Visualization:" + value: Grafana, Superset, Metabase, Lakeview, Power BI, Tableau, Matplotlib, D3.js + - name: "Operating systems:" + value: Mac OS, Windows, Ubuntu, Raspberry Pi OS, Linux Mint - title: Others type: list diff --git a/_news/announce_whitecoat.md b/_news/announce_whitecoat.md new file mode 100644 index 0000000000000..8db626d549543 --- /dev/null +++ b/_news/announce_whitecoat.md @@ -0,0 +1,7 @@ +--- +layout: post +date: 2024-05-01 00:00:00+0800 +inline: true +--- + +I joined [WhiteCoat](https://www.whitecoat.global) as a Data Scientist, working across the full data function — from data-platform engineering to company-wide AI transformation! diff --git a/_pages/about.md b/_pages/about.md index b5b00cd08f758..a6d0e06731bae 100644 --- a/_pages/about.md +++ b/_pages/about.md @@ -3,15 +3,14 @@ layout: about title: about nav-title: about permalink: / -description: Data Scientist • Garena • Sea +description: Data Scientist • WhiteCoat profile: align: right image: prof_pic.jpg address: >

Résumé/CV

-

1 Fusionopolis Place #17-10

-

Singapore 138522

+

Singapore

news: true # includes a list of news items @@ -19,7 +18,9 @@ selected_papers: true # includes a list of papers marked as "selected={true}" social: true # includes social icons at the bottom of the page --- -Hello 👋 Welcome! I am a Data Scientist at [Garena](https://www.garena.sg), and I love to explore data-driven approaches to solve real-world problems. +Hello 👋 Welcome! I am a Data Scientist at [WhiteCoat](https://www.whitecoat.global), a Southeast Asian digital health platform (SG/MY/PH/HK/ID), where I work across the full data function end to end — data engineering, analytics, data science, and company-wide AI transformation. I love using data-driven and agentic-AI approaches to solve real-world problems. + +Before WhiteCoat, I was a Data Scientist at [Garena](https://www.garena.sg) (Sea Ltd), building recommendation systems for an online video live-streaming and community platform. I got my M.Eng. from [Singapore University of Design and Technology](https://www.sutd.edu.sg) [ISTD Pillar](https://istd.sutd.edu.sg), advised by [Alexander Binder](https://www.visual-intelligence.no/people/alexander-binder) and [Kwan Hui Lim](https://sites.google.com/site/limkwanhui/). I did research on explainable artificial intelligence (xAI) methods for interpreting deep learning models. diff --git a/assets/pdf/CV.pdf b/assets/pdf/CV.pdf index 8e465bac98f30..c9f51d2a0ebcd 100644 Binary files a/assets/pdf/CV.pdf and b/assets/pdf/CV.pdf differ