Hi, I’m Jingtao Scott Hong
Graduate student in Business Analytics at Columbia University with a Computer Science background from the University of Virginia. Skilled in AI, data science, and software engineering, with a focus on developing robust, scalable solutions. Experience includes building AI-powered automation platforms, optimizing data architectures, and creating full-stack web applications in roles at HireBeat and KPMG Shanghai. Led projects such as an Azure OpenAI-driven environmental compliance assistant, utilizing advanced NLP, graph databases, and embedding techniques. Proven ability to combine machine learning, data engineering, and software development to create impactful, data-driven business solutions.
Experience
HireBeat
Data Scientist and Artificial Intelligence Engineer Intern
New York, NY | Jun 2024 – Present
- Spearheaded the development of a Python-based LLM workflow automation platform, featuring integrations with leading APIs such as Google and Microsoft.
- Architected sophisticated data structures, refined LLM prompts, and implemented benchmarking and testing protocols, building databases with SQL and PostgreSQL.
- Engineered an advanced Graph Database utilizing a RAG structure on AWS, significantly enhancing data retrieval efficiency and accuracy.
KPMG Shanghai
M&A Advisory Associate Research Intern
Shanghai, China | Jun 2023 – Aug 2023
- Conducted industry research across sectors like pharmaceuticals and 3D printing, identifying over 100 companies for analysis.
- Authored white papers detailing market trends and financial performance.
- Participated in client interviews, contributed to crafting questions, and summarized discussions for M&A advisory support.
- Prepared presentation decks summarizing research and interview insights for client engagements.
UVA DevHub
Machine Learning Engineer and Software Development Intern
Charlottesville, VA | Jun 2022 – May 2023
- Developed a full-stack web application for clients using Django, ReactJS, and Bootstrap, incorporating features like keyword research.
- Enhanced performance and security for the client’s website through interface improvements and online data storage integration.
- Utilized TensorFlow to create predictive pricing and maintenance models, reducing IT downtime by 9%.
- Engineered and deployed an automated data pipeline using AWS Lambda and Python, optimizing data processing times and enhancing data management efficiency.
Research & Projects
EcoLegal Assistant: LLM-Driven Environmental Compliance Solutions
New York, NY | Jan 2024 – Apr 2024
- Capstone Project Leader with GHD INC.
- Pre-processed a comprehensive dataset derived from Title 40 of the Code of Federal Regulations and web-scraped 1M+ text, graphs, 100+ tables, and 2000+ formulae as relevant information, storing in a Neo4j graph database.
- Designed and deployed an Azure OpenAI-powered LLM solution for environmental compliance, using sophisticated prompt engineering, embedding matching, and Cypher querying.
- Conducted 100+ experiments to fine-tune 10+ hyperparameters, implementing advanced techniques in NLP, embeddings, and graph-based querying.
Machine Learning Research: SoK: Pitfalls in Evaluating Black-Box Attacks
Charlottesville, VA | Aug 2022 – Apr 2024
- Group Research advised by Professor David Evans & Yuan Tian of UVA.
- Designed a comprehensive platform that reproduces 30+ SOTA adversarial attacks, implementing 10+ kinds of adversarial attacks (3000+ lines of code).
- Paper accepted by the 2nd IEEE Conference on Secure and Trustworthy Machine Learning.
- Link to Paper
Leadership Experience
Mainland Student Network | External Vice President
Charlottesville, VA | Oct 2019 – May 2023
- Outreached and maintained connections with over 20+ organizations for events and organizational funding.
- Led the organization’s publicity efforts, managing 3+ social media accounts and providing high-level guidance.
- Supported logistics, outreach, and publicity for 20+ events, developing and maintaining 8 sponsorship relations.