Grant Chen Email & Phone Number

United States

• Implemented data-driven Ideal Customer Profile (ICP) by advanced analytics and machine learning, collaborating cross-functionally with Product, Marketing, and Sales teams to integrate into Salesforce• Discovered market insights across global market leveraging customer segmentation, identifying growth opportunities and designing targeted strategy that increased new market penetration by 15%

Chicago, Illinois, United States

• Implemented a reproducible pipeline for identifying and visualizing data integrity in NORC’s label prediction models and NORC’s vendor data, targeting inaccurate labels and underrepresented populations to improve the representativeness of survey results• Analyzed biases in predictions for African American individuals of NORC’s labels prediction models by cross-referencing census tables and AmeriSpeak data, focusing on addressing misinformation and underrepresentation in demographic distribution

Chicago, Illinois, United States

• Headed team collaboration with Chicago Trading Company, employing prompt engineering on GPT4 for automating financial market tweet labeling and implemented LLM for sentiment scoring, reducing 16% of Mean Squared Error (MSE) in stock prediction• Supervised collaborative development of Stable Diffusion generative model with Fermi Laboratory, achieving 92% accuracy in approximation of physics experiments• Led the implementation of AI-enhanced policy management system in Argonne National Laboratory, leveraging Large Language Models and Neo4j graph database to achieve 80% reduction in manual effort for information retrieval and updates

Hsinchu City, Taiwan, Taiwan

• Enhanced recommendation model by fine-tuning Large Language Models (LLMs) with HuggingFace for precise information extraction and accurate embeddings from product text descriptions• Engineered end-to-end data pipeline by utilizing Spark for text preprocessing and Elasticsearch for unstructured data management, increasing 400% in data processing speed• Deployed recommendation model on AWS EC2 using Flask and Docker, decreasing 67% response time and accommodating 100,000+ users during a high-traffic exhibition

Taipei City, Taiwan

• Enhanced E.SUN Bank’s (Top 3 financial institutions in Taiwan) Mutual Fund Recommendation System by Neural Collaborative Filtering by integrating user metadata including Know Your Customer (KYC) data, purchase history, and fund feature analysis,boosting 65% in revenue• Established Multi-Behavior Recommendation Model with novel embedding design and submitted to IJCAI conference• Conducted in-depth analysis and delivered valuable insights from 30+ papers to non-technical stakeholders, focusing on potential applications in finance domain

Taiwan

• Coordinated with cross-functional teams in Product, Marketing, IT, and Sales to transform actionable insights from customer segment and churn prediction model into effective strategies, increasing 36% financial product sales• Established and maintained Tableau dashboards for real-time monitoring of marketing campaigns and sales performance, reducing 76% daily report generation time• Implemented a combination of Selenium crawler and Natural Language Processing to label 20,000 merchants, reducing 80% manual processing time

Taiwan

• Deployed price forecasting model in AWS SageMaker, establishing retraining pipeline for continuous improvement• Conducted multiple end-to-end A/B tests to enhance the user interface and evaluate new features, achieved 25% increase in user engagement and 30% in conversion rate• Designed and managed Tableau dashboards for agricultural wholesalers and retailers, providing instant visualization of crop price trends and trade volume fluctuations

Master Of Science - Ms, Statistics

Bachelor'S Degree, B.S. In Statistics And Minor In Management Information Systems

Overall GPA: 3.84 / 4.00 Honor: Academic Excellence Award (top 5% of class in semester) Courses: PyTorch and Machine Learning, R computing.