Every time a customer types a search on homedepot.com, our sophisticated system springs into action to surface the right products in the right order. Getting customers to the right product sounds simple. So what does it take behind the scenes? Siawpeng, a Lead Data Scientist, helps build the technology that powers our digital shopping experience. His work shapes how millions of online shoppers find the products that they need, when they need them.

Lead Data Scientists, like Siawpeng, design and advance the neural retrieval and ranking systems that power product search on our website. This technology determines which products appear, and in what order, every time a customer searches our digital catalog.

Siawpeng’s work centers on deep learning and natural language processing. He works with Large Language Models (LLMs) and Small Language Models (SLMs), uses knowledge distillation to make models faster, and combines clickstream data with generative AI to power features like the product badging platform. He builds and deploys on Google Cloud Platform and leverages a suit of generative AI productivity tools—including Claude, Gemini, coding assistants, and agentic workflows—to accelerate the development cycle.

“Our major priority is tailoring search and discovery to the unique needs of our Pro customers, while supporting the needs of our broad Do-It-Yourself customer base,” Siawpeng shares. “We leverage LLMs to strategically focus on personalization and enhance product relevance for each search.”

This work doesn’t happen in a silo. “I work closely with teams across the company,” Siawpeng shares. He collaborates with Product Managers, Merchants, Software Engineers, Business Intelligence Analysts, and more. Working with partners helps him to understand customer pain points, business needs, and allows him to test and scale solutions before they reach customers.

When a customer searches homedepot.com, they’re looking for something specific and they want to find it quickly. Siawpeng’s work helps make that happen. By optimizing search retrieval and ranking, his team directly shapes whether a customer lands on the right product or has to keep looking.

The results speak for themselves. A search ranker Siawpeng built delivered a strong lift in sales, along with double-digit basis point gains in both click-through and search reformulation rates. Customers found what they needed faster and with less friction. His team then integrated that ranker into a semantic retrieval engine, shifting homedepot.com from traditional keyword-based matching to neural semantic search.

As a DIYer, Siawpeng knows the importance of his work from both the customer and Data Scientist perspective. He shops for the same tools and products for his own home projects. “Whenever we optimize our search and discovery systems, I know that I’m not just solving an abstract technical problem,” he shares. “I’m making the experience better for millions of shoppers just like me.”

“Because of our scale, even incremental algorithmic improvements translate into millions of dollars in impact and a better experience for millions of shoppers.”

Beyond the technology, he points to our culture. “Mentorship is an important part of who Home Depot is,” he shares. “Strong mentors and exceptional leaders have guided my career.” He gives back by supporting interns and Senior Data Scientists as they sharpen their technical skills and navigate complex system designs.

Looking ahead, Siawpeng is confident about what’s next for The Home Depot. “Our search team is uniquely positioned to drive the next era of AI-powered commerce,” he says. “I can’t wait to see the next-generation systems we build together.”

Siawpeng first learned about our internship through his PhD advisor at Georgia Tech, where his research focused on machine learning and Natural Language Processing (NLP). “Home Depot was tackling search retrieval and ranking at a massive scale,” Siawpeng shares. “It was the perfect opportunity to take the theoretical methods I was researching and apply them to real business problems with millions of users.”

After completing his Machine Learning/NLP internship and earning his PhD, Siawpeng joined The Home Depot full-time as a Senior Data Scientist. In 2025, he was promoted to his current role as a Lead Data Scientist, where he leads technical direction across multiple online search initiatives.

Explore open roles on our Data Science teams and apply today!