Michelle Wang

AI-product Builder

Current: Founder of AI Daily View More Education: Columbia University View More Email: wang.michelle.yi@gmail.com Phone: 917-847-8851 LinkedIn: www.linkedin.com/in/michelleyiwang

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About Me

AI-product builder and full-stack engineer with 7+ years shipping production systems from 0-to-1 launch through scale. Founder of AI Daily (aidaily.now), an LLM-powered news platform I solo-built end-to-end across the LLM pipeline, full-stack, and growth, now reaching 50,000+ subscribers across the global AI industry. Hands-on across the entire AI application stack (LangChain, OpenAI APIs, RAG, vector stores, embeddings, prompt engineering) with the engineering depth (Python, Java, React, Node.js, Spring Boot, AWS/GCP) to turn AI prototypes into products that ship, scale, and earn.

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Personal Details

Focus: Full-Stack Development
Experience: 7+ Years
Location: Mountain View, CA
Visa Status: Green Card Holder

Work Experience

From Feb 2025 To Present

(1 Year 3 Months)

AI Daily Inc. Mountain View, CA

Founder

Solo-built and scaled an LLM-powered AI news platform delivering 6 curated briefs in a 5-minute weekday read; sole owner of AI engineering, product, growth, and ops.

LLM Pipeline: Architected an end-to-end AI content pipeline on Python + LangChain + OpenAI APIs, ingesting 500+ daily AI stories, ranking by signal, and auto-summarizing into 6 high-density briefs; cut editorial cycle time ~70% and removed humans from the critical path.
Full-Stack Build: Designed and shipped the platform solo on a capital-efficient stack, owning React frontend, Node.js backend, email infrastructure, analytics, and archive site from prompt design to production deployment.
Audience Growth: Compounded readership 5x QoQ to 50,000+ subscribers in <15 months at open rates ~2x the industry benchmark; ran 40+ A/B tests on subject lines, send times, and content mix, lifting opens 25% and tightening retention cohorts.
Production Reliability: Shipped 300+ consecutive weekday editions with a strict morning publish SLA, built monitoring, fallback paths, and automated QA so a one-person operation behaves like a reliable platform.
AI Fluency: Daily editorial coverage of model releases, agent frameworks, and industry moves keeps technical context sharp, from frontier labs to applied AI in marketing, search, and consumer products.

From Aug 2025 To Present

(10 Months)

Sachi Cares Inc. Mountain View, CA

Full-Stack Engineer & Technical Program Manager

Built and scaled a two-sided childcare marketplace, owning core systems and AI-powered product features.

AI Features: Shipped AI-powered semantic matching and automated session summaries, driving up to 50% lift in user activation and retention.
Platform Architecture: Built core marketplace systems (auth, booking, payments, verification) in React and Node.js/Spring, raising onboarding-to-booking conversion by ~30%.
Scalable Systems: Designed high-availability services for real-time scheduling and transaction workflows, holding consistent performance under growing user load.
Performance Optimization: Tuned PostgreSQL/PostGIS and trimmed API hot paths, accelerating search and booking flows.
Execution Velocity: Delivered end-to-end features in Agile sprints, lifting engineering throughput ~25% against a $1M+ GMV product roadmap.

From Nov 2022 To Jul 2023

(8 Months)

First Republic Bank San Francisco, CA

Data Scientist Lead, Data Analytics & Automation

Engineered data tools and infrastructure powering Internal Audit's analytics strategy and automation.

Pipeline Engineering: Built scalable Python/Snowflake ETL pipelines as reusable building blocks across audit workflows, boosting data accessibility 60% and slashing query latency 40%.
Tool Delivery: Shipped 8+ internal analytics tools and automation pipelines via Agile sprints with auditors and engineers, eliminating 50% of manual reporting overhead.
Data Visualization: Built 12+ interactive Tableau dashboards tracking collateral valuations and compliance gaps across 3,000+ real estate loans, surfacing $25M+ in previously undetected exposure.
Code Optimization: Refactored legacy scripts and standardized 1M+ records across 500+ fields, accelerating downstream analysis 35% and cutting data prep from days to hours.

From May 2020 To Nov 2022

(2 Years 6 Months)

Atomyze LLC Greenwich, CT

Data Scientist Lead, Product

Led full-stack delivery of blockchain-based digital-asset products from concept through production launch.

Platform Launch: Shipped a digital-asset tokenization and trading platform end-to-end; managed delivery via Jira and raised engineering velocity 25% through structured sprint planning and CI workflows.
Scrum Execution: Led a 2-engineer team and partnered with C-suite to design and deliver smart-contract-based commodity tokenization, delivering core features 30% ahead of original timelines.
Product Specs: Authored 20+ PRDs aligning feature development to customer needs and revenue goals across 8+ product epics.
Growth Engineering: Built and launched the company's public website with Google Analytics instrumentation; grew organic traffic 15% and cut bounce rate 20% via UX and SEO iterations.

From Jul 2015 To Jun 2018

(3 Years)

CITIC Asset Management Co., Ltd. Beijing, China

Senior Manager, Investment Analytics

Led investment analytics at one of China's largest asset managers, building tools that supported strategic capital deployment.

Team Leadership: Directed a 3-person Beijing-based team building 6+ internal analytics tools and automated workflows, powering investment decisions across 50+ healthcare-sector deals.
Financial Modeling: Built scalable IRR/ERV modeling frameworks evaluating 200+ investment opportunities annually, enabling ~$370M in annual loan deployment.
Data Engineering: Spearheaded metadata analysis and data-classification integration across banking datasets; introduced automation pipelines that cut manual reporting effort 40%.

Education

Columbia University

M.S., Applied Analytics (GPA: 4.1/4.0)

Relevant Courses: Machine Learning, SQL & Relational Database, Advanced Python for Data Analysis, Analytics with R

Aug 2018 - Dec 2019

University of Southern California

B.S., Business Administration (GPA: 3.5/4.0)

Sep 2012 - Dec 2014

Technical Skills

Frontend

React 95%

JavaScript 95%

TypeScript 90%

HTML 95%

CSS 95%

jQuery 85%

Next.js 90%

Ant Design 85%

Backend

Java 95%

Python 95%

Spring Boot 90%

Hibernate (JPA) 85%

Node.js 85%

Express.js 85%

SQL (PostgreSQL, MySQL) 95%

NoSQL (MongoDB) 80%

Cloud & DevOps

AWS 85%

GCP 85%

CI/CD (GitHub Actions) 90%

Docker 90%

Git 95%

Vercel 85%

Tools

Claude 95%

IntelliJ IDEA 95%

VS Code 90%

Codex 90%

Postman 95%

Tableau 95%

AI, Cloud & Frameworks

AWS (Amplify, RDS, App Runner)

Google Cloud (Cloud Run, Cloud Storage)

LangChain

GPT-3.5 Turbo

OpenFeign

Gradle

Jenkins

Technical Projects

Staybooking

https://staging.d3q2arguljputk.amplifyapp.com

An online stay rental application based on React and Spring Boot

Designed and built a responsive web application using React; Bootstrapped the development with Ant Design.
Developed and maintained RESTful APIs and Spring Boot-based microservices, enabling users to create, search, reserve, and manage stay listings.
Leveraged PostgreSQL, PostGIS, and Hibernate (JPA) for storing user data and geospatial queries; used Google Cloud Storage for managing uploaded media files.
Implemented stateless and scalable user access using Spring Security with JWT token-based authentication.
Deployed the backend to Google Cloud Run, and the frontend to AWS Amplify, with CI/CD integration using Gradle and Git Action for automated builds and delivery.

Twitch+

https://mcrawjf52p.us-east-2.awsapprunner.com/

A personalized Twitch resources recommendation engine

Built a web page with user-friendly UX using React and Ant Design; Stored game data in MySQL database hosted on AWS RDS; Conducted CRUD operations with Spring Data JDBC.
Integrated the Twitch API using OpenFeign to fetch real-time Twitch content and built RESTful APIs for frontend-backend communication.
Implemented Spring Security for user authentication and developed a content-based recommendation system using users' favorite collections.
Optimized performance with Spring Caching + Caffeine and ensured reliability through unit testing.
Dockerized the application and deployed it seamlessly on AWS App Runner for public access.

Next AI

https://staging.d3szzyszv8ohsw.amplifyapp.com/

A full-stack web-based Q&A AI agent for PDF document queries

Created an interactive conversational UI leveraging React and Ant Design, enabling users to effortlessly upload and interact with PDF documents in real-time.
Implemented RESTful APIs via Express and Node.js and optimized for high-performance request handling.
Utilized an in-memory vector store to cache generated embeddings for efficient retrieval.
Integrated OpenAI's GPT-3.5 Turbo API and LangChain technologies, resulting in a sophisticated AI Agent capable of document loading, splitting, storage, retrieval, and output functionalities.

Global Terrorism Analysis

A PostgreSQL-powered analytics system for identifying terrorism patterns

Cleaned dataset with 180,000+ entries and 135 variables using Python; designed a relational schema in 3NF with ER diagram including all integrity constraints and triggers.
Extracted 23 key variables related to the project scope from original dataset, performed data cleaning and aggregation to transform the selected data, and staged the data on destination database by creating a connecting engine with PostgreSQL server.
Built an interactive dashboard visualizing targeted terrorism KPIs using Metabase, and summarized findings in a report presented to the United Nations Office of Counter-Terrorism.

YouTube Trends

A Python-based analytics project uncovering factors behind YouTube viewership

Implemented data-cleaning process on 40,000+ observations and 17 variables including both structured and unstructured data; transforming fragmented datasets into a unified dataset for streamlined analysis.
Utilized Pandas and Matplotlib libraries to visualize data insights; plotted correlation matrix and visualized the result using heatmaps to identify statistical relationships between numerical and Boolean variables.
Applied sentiment analysis on video titles, genres, and description keywords to identify and monitor viewer sentiment qualities and computed word-clouds to represent frequency counts and importance of words.

Contact Information

Email wang.michelle.yi@gmail.com

Phone 917-847-8851

Location Mountain View, CA 94043

LinkedIn linkedin.com/in/michelleyiwang