Peiyuan Wei

CEO

Singapore, Singapore0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Proficient in Python and data analysis tools.
Experience in building knowledge bases for AI applications.
Strong background in exploratory data analysis and visualization.

Stackforce AI infers this person is a Data Engineer with a focus on AI and analytics in the healthcare sector.

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Skills

Core Skills

PythonData AnalysisData ManagementMachine LearningData Visualization

Other Skills

PandasNumPySeabornPlotlyTableauReact.jsPivot TablesMicrosoft ExcelLarge Language Models (LLM)RedisGo (Programming Language)PostgreSQLMongoDBKafkaAmazon Web Services (AWS)

About

A recent graduate of the University of Minnesota with a Bachelor of Science in Computer Science, currently pursuing a Master of Science in Data Science and Machine Learning at the National University of Singapore (expected 2026). Most recently worked as an AI & Analytics Intern at China Youth Online, leveraging Python, Pandas, and NumPy to clean and structure extensive datasets for large language model integration. Proficient in exploratory data analysis using Seaborn and Plotly, with experience in creating effective visual dashboards using Tableau to enhance data insights. At China Youth Online, supported the refinement of a Traditional Chinese Medicine knowledge base by analyzing and categorizing question types to optimize data representation. Contributed to the evaluation of LLM responses, focusing on reducing hallucination and improving accuracy through collaborative efforts. Committed to applying strong technical skills and a passion for data-driven decision-making to solve complex problems and drive innovation in diverse, forward-thinking organizations.

Experience

Siemens

IT Finance Transformation

Jan 2026 – Present · 2 mos · Singapore

PythonPandasNumPySeabornPlotlyTableau+2

China youth daily

AI & Analytics Intern

Oct 2023 – Dec 2023 · 2 mos · Beijing, China · On-site

Cleaned and structured 30k+ Traditional Chinese Medicine Q&A pairs using Python, Pandas, NumPy to build a consistent knowledge base for LLM integration.
Conducted EDA with Seaborn and Plotly to classify question types and identify underrepresented topics for dataset refinement.
Evaluated LLM responses pre- and post-knowledge augmentation, measuring hallucination reduction through accuracy metrics and Tableau visual dashboards.