Cake Talent Search

Wang Wen Shang Tainan City, Taiwan || [email protected] Summary & Career Goals Computer Vision & AI Expertise: Over 12 years of experience in image processing, object detection, 3D reconstruction, and AI-driven automation. Machine Learning & Data Processing: Expanding expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and MLOps to enhance intelligent data-driven solutions. Python & Linux Proficiency: Proficient in Python, C++, OpenCV, and Halcon, with a strong focus on performance optimization and Ubuntu-based development. Cloud & Containerization: Skilled in Docker-based deployments and integrating scalable applications with modern cloud technologies. Distributed

曲培文 數據科學家 擁有五年以上數據科學及機器學習經驗 ， 曾於美國頂尖金融機構以Python開發與部署多項機器學習模型，並領導多項跨部門專案，提供 不同單位 數據驅動的解決方案 ，以優化公司業務流程並降低風險 。 技能: Python, SQL, AWS, Git, Tableau, Agile 語言: 英

SQL queries to enhance processing speed and efficiency. • Streamlined the CI process to enable automated Git merge operation. • Developed a binary search-based logger to improve large file download speed. • Automated operational workflows by creating key scripts in Java. National Taiwan Normal University Graduate Student SeptAug• Natural Language Processing (NLP) Research Project: Focused on sentiment analysis to automatically identify positive or negative sentiments from user reviews. • Deep Learning Model Application: Utilized Convolutional Neural Network (CNN) architecture to enhance the accuracy of sentiment classification. • Word Embedding Techniques: Conducted in-depth research on word embedding techniques

improving insights delivery speed by 20%. - Designed a high-performance data warehouse on AWS, improving cross-team data accessibility and reducing query times by 35%. EDUCATION National Taipei University of Technology • Master’s Degree in Electronic Engineering MaySep 2019 | Taipei, Taiwan • Specialized in developing deep learning models for Natural Language Processing (NLP). • Developed classification systems for speech/audio using deep learning techniques. • Conducted research on image classification and recognition through deep learning methodologies. CERTIFICATIONS • Google IT Automation with Python, Coursera - FebPATENT • ABNORMAL SOUND DETECTION METHOD AND APPARATUS (USA1) - FebSKILLS Programming & Frameworks : Python, TensorFlow, Keras

hours daily for medical professionals. Calibrated and deployed a machine learning regression model for waveform predictions, enhancing accuracy for 500+ blood pressure monitors. Research Assistant Department of Computer Science, NCCU • August 2019–July 2020 Conducted opinion mining on 2,500 wine reviews using Transformer-based pre-trained language models. Delivered NLP coursework guidance to over 70 students as a Teaching Assistant. Account Manager Leo Burnett Taiwan • February 2017–May 2019 Orchestrated rebranding strategies for Chia Shin Cement Group, resulting in the only successful brand declaration campaign in five years. Localized branding materials and executed

future organizational growth - Successfully retained a 4.6-star user rating and boosted job application rates by 10%. - Collaborated with the product owner, UI/UX designer, and sales department to design the AD system. • AI Implementation: Created an AI tool to convert UI test cases from natural language into UiAutomator2 scripts, seamlessly integrating them into the CICD process. This resulted in a 90% acceleration UiAutomator2 test case generation. • Technology Introduction: - Flutter: Developed an in-house App Dashboard to consolidate Android/iOS/backend CICD build statuses and test report outcomes. Single-handedly

with problem solving, I have strong determination to succeed and hope to make a contribution to every opportunity. Data Engineer Hsinchu, TW [email protected] Skills Big Data Engineering Rich knowledge in NoSQL , skilled in RESTful search API and distributed analytics engine ElasticSearch . Experienced in multilingual Natural Language Processing , working on reliable data pre-processing and data cleaning. Deep Learning Leading team members to do research and build Machine Learning models, further designing prototypes on application system. Utilizing Deep Learning methods (CNN/RNN) to process heterogeneous documents and develop systems for market analysis