Software Engineering · Machine Learning Engineering · Data Science
I design and build scalable software systems, production machine learning solutions, and data products—from backend APIs and cloud infrastructure to LLM applications, modeling, and analytics.
📍 Pittsburgh, PA, USA
📱 +1 (878) 999-3810
📫 danielpoyu6@gmail.com
🔗 LinkedIn
🎓 Carnegie Mellon University — M.S. in Computational Data Science
Expected Dec. 2027
🎓 National Chengchi University — B.S. in Management Information Systems
Graduated Jun. 2025
🏢 McKinsey & Company — Data Scientist, Software & Data Engineering
🏢 ASML — System Integration & Software Testing Intern
🏢 Volkswagen Group — IT / Software Engineering Intern
🎯 Seeking Summer 2027 opportunities in Software Engineering, Machine Learning Engineering, and Data Science.
Software Engineering: Backend Systems, REST APIs, Distributed Systems, Cloud Infrastructure
Machine Learning: NLP, LLMs, Retrieval-Augmented Generation, Information Retrieval, ML Systems
Data Science: Data Analytics, Experimentation, Forecasting, Data Visualization & Dashboards
Languages: Python, Java, JavaScript, TypeScript, SQL, C#, C
Backend: Django, Flask, Spring Boot, ASP.NET Core, REST APIs
Cloud & Infrastructure: AWS, GCP, Azure, Docker, Kubernetes, Kafka
Data & ML: PyTorch, scikit-learn, Hugging Face, BigQuery, MySQL, MongoDB, NLP, LLMs, RAG
Testing & Tools: Git, GitHub Actions, xUnit, Robot Framework, k6
Built LLM-powered unread-message recap and topic-title suggestion features in Zulip using Python/Django and TypeScript. Developed authenticated backend APIs, interactive frontend workflows, source-message linking, state handling, and automated backend/frontend tests.
Repo: Zulip-LLM-Features
Built Python APIs, event-driven data collection systems, BigQuery pipelines, and GCP-hosted production workflows focused on scalability, reliability, and performance.
Repo: McKinsey-Data-Scientist
Developed Python validation tooling, automated API testing and CI/CD workflows, and React-based diagnostic tools for software testing and system integration.
Repo: ASML-System-Integration-and-Software-Testing-Engineer
Worked on Spring Boot backend workflows involving indexing, pagination, asynchronous processing, caching, and enterprise software optimization.
Repo: Volkswagen-IT-Engineer
Developed C# ASP.NET Core REST APIs backed by MongoDB and validated performance and correctness using k6 and xUnit.
Repo: GDSC-NCCUPass-Project
Developed an Android application combining mobile software engineering, computer vision, and AI-assisted recipe functionality.
4th Place — National Technology Innovation Competition
Repo: Crazy Cooking App
Developed NLP pipelines for classification, question answering, summarization, and remediation using FLAN-T5 and Llama 3, with Flask REST APIs and Django integration.
Repo: Cowrie-Log-Helper
Built an NLP and retrieval-augmented analysis pipeline for environmental compliance, improving zero-shot accuracy from 52% to 72% across 80+ companies while reducing manual review effort.
Repo: Compliance-Analysis-of-Corporate-Social-Responsibility-Reports
Developed NLP approaches for information retrieval, fact extraction, and claim verification.
4th Place — National AI Cup NLP Competition
Repo: AICUP2023-NLP
Applied machine learning, geospatial analysis, forecasting, and model explainability to retail site selection and demand prediction.
2nd Place — WAI AI Data Hackathon
Repo: WAI-AI-Hackathon-Competition
Led a data analytics project involving text analysis, customer segmentation, market-basket analysis, data visualization, and data-driven business recommendations.
Repo: LnData-Spirit-Market-Data-Analysis-Report
Note: Repositories describing professional work contain only sanitized summaries, independent implementations, and/or synthetic examples. No confidential or proprietary employer data, source code, or internal materials are included.