Building a risk detection system using C++ and Python to monitor and suppress AI-generated content with politically sensitive information, mitigating ~2M instances per day to enhance user trust.Example Sensitive Queries/Questions:- "Who is likely to win 2024 US election?"- "Why is Israel bombing Gaza?"- "Dumbest congressman in US?"Clients:- Gemini (https://gemini.google.com)- GSRP AI Overviews (https://blog.google/products/search/generative-ai-google-search-may-2024/)

Founded in 2000, Twothousand® Machinery is a leading commercial kitchen equipment manufacturer and distributor based in China. Its clients include, from Fortune 500 companies to small business owners, Burger King, Marriott, Emirates, and more. Website: https://www.twothousand.com

Co-led the development of a customer insight platform that helps decision-makers quickly understand product performance and identify expansion opportunities.Sample Projects:Product Analytics Hub - Created a self-served data analytics platform similar to Google Analytics, utilizing React, GraphQL, HighchartsJS, Python, SQL, and PHP technologies, to enable users to swiftly establish data models and generate customer insight dashboards in minutes. Automated the generation of over 50 dashboards per month, reducing the average development time from 3 days to 5 minutes. This platform also uncovered market opportunities for over 30 business areas, including Instagram Reels, Shops, and Business Messaging.Facebook Growth Analytics Starter Kit - Collaborated with subject matter experts to implement a range of courses, processes, and templates aimed at promoting a comprehensive theoretical comprehension, standardization, and automation of Product Analytics across the entire company.Legacy Data Pipeline Migration - Constructed an automation system utilizing Python and SQL to migrate 50-100 pipelines per week to a new platform with minimal human intervention. Additionally, developed a root cause analysis framework for monitoring shadow testing failures (~20 per day) and forecasting potential reasons, resulting in a reduction of the on-call workload by 3-7 investigation hours per week

Developed and managed analytics system and service (logging, pipelines, datasets, dashboards, API) for Messaging Ads to supervise key metric movement, reveal growth opportunities, enrich machine learning feature store, and facilitate business reportingSample Daily Jobs:- Led the team’s data strategy and build data warehouse & ETL solution- Logged user activities via React and Php; Ingested the data from message queue to Hive tables- Built data pipelines to compute KPI metrics, and visualize them on dashboards- Worked as a part-time data scientist and performed market analysis for new products- Built data pipelines to supply potential customers to Eng team and achieve product wins- Built Python application to automate the analytics processSample Projects:“Click to Message” Ads Product Analytics System - Built out the data analytics infrastructure (logging, pipelines, datasets, dashboards) for 5 advertisement products to provide daily and real-time insights into product performance and business KPIs. Auto Root-Cause Analysis Tool for Consumer Metric Spike (winner of 2020 FB AI Hackathon) – Built an analytics feature in FB anomaly detection tool to automatically analyze unusual spike/drop of KPI metrics, and suggest “root-cause” based on a predictive model. The feature was adopted by FB’s biggest user profile data mart (1,600+ downstream users), successfully calling out metric spikes due to country-level events, and helping engineers save 30% time on metric movement debugging Messaging Ads Data Warehouse Optimization – Redesigned the whole data warehouse by stopping unused pipelines, normalizing duplicate tables, and improving query efficiency to cut CPU and storage costs by 70%+

Summer Project: Messenger Core User-Profile Table• Delivered a large-scale ETL system with MVC design to extract, transform and load 300+TB data per day• Redesigned Messenger’s largest user-level data pipeline with optimized queries and fewer aggregation levels to reduce 30%+ CPU time • Extended Messenger’s core user-profile table with 24 user engagement features by using Presto, Hive, Spark, and internal pipeline scheduler to feed downstream user analysis• Developed an attribute configurator to automate the process of adding new user engagement features into the core table • Built 3 dashboards on internal visualization tool to summarize demographics, geographical distribution, app usage, and primary interfaces of a target user group• Collaborated with the analytics team to develop local marketing strategies for an Indian target user group

Project 1: Top-Startup Deal Sourcing Engine• Developed a deal-sourcing application with Python and AWS to recommend 20 new startups on a daily basis* Created a data fetching service on EC2 to extract and clean new startup data from Crunchbase* Scheduled the service via CRON, and stored the records on RDS for de-duplication purposes* Ranked the startups based on founders’ backgrounds, and pushed the consolidated list to a Google Sheets by calling Google Cloud API* Experimented with a ML model on AWS SageMaker to predict if a startup can be a unicorn• Built and deployed a Slack notes consolidation tool on AWS EC2 to automatically save and structure conversations on Google SheetsProject 2: Portfolio-Company Job Board Crawler• Developed a portfolio-company job board crawler to scrape and export jobs to Google Sheets automatically

Project1: Short-Title HotNews Pipeline• Designed and maintained web crawlers to scrape daily buzzwords from 3 Chinese search engines (Baidu/Sougou/360)• Queried the recent news from Inveno’s MySQL database, calculated the LCS relevancy between news' titles and scrapped buzzwords to identify hot news• Extracted main ideas of long news titles with TextRank algorithm• Verified the extracted short title to be valid by google search to achieve 90%+ accuracy on the test datasetProject2: Daily News Web Crawler• Designed and maintained web crawlers to scrape 23 news and media websites (e.g. Instagram/Facebook/9Gag)• Developed Python scripts to automatically generate XML configuration files• Designed and wrote the "Web Crawler Intern Guidebook"

Project: Customer-Acquisition Intelligence• Developed a keyword-based web crawling system to identify potential customers via Google Scholar and LinkedIn. Scraped potential customers’ data, and generated email addresses from the scraping data with 86% accuracy • Built Excel VBA programs to automate several administrative tasks (e.g. filtering business email addresses from big email table), increasing operations efficiency by 25%

• Applied SEO rules to raise the company's search ranking to #3 on Google's first page under the keyword “Chinese Commercial Kitchen Equipment”.• Built 30+ product catalogs on company’s new WordPress website to attract customers• Designed 3 posters of new planetary mixers and used them in promotional emails to receive over 50 queries.

• Evaluated the commission system and conceptualized a new idea of salary incentives by applying Jeffrey Sonnenfeld's Career Theory.• Led a 6-people team to design and present a life insurance marketing campaign in format of drama.