YOUNG JIN KIM

Experienced in data-driven policy and risk analysis through roles at the National Assembly Budget Office and PwC Korea. At the Assembly, contributed to national economic reports using econometric modeling and policy evaluation. At PwC, supported the development of LLM-based AI models for internal control and fraud risk detection, integrating unstructured data with cloud-based systems. Skilled in translating complex data into actionable insights for both public and corporate sectors.

• Conducted master's thesis titled "Investor Responses to Emotion in Corporate Social Media Mentions", integrating behavioral economics and NLP to analyze the effect of emotion on excess returns using BERT-based sentiment classification.
• Presented thesis findings at the 2023 Korean Operations Research and Management Science Society (KORMS) Conference, Data Analytics Session.
• Participated in the LG H&A Brand Social Listening Enhancement Project (Phase 2) as a research assistant, applying aspect-based sentiment analysis (ABSA) to classify extreme consumer feedback and derive insights for product improvement strategies.
• Co-authored national economic reports at the National Assembly Budget Office, including “2024 Korean Economy” and “Policy Tasks for Sustainable Growth”, contributing econometric and time-series analysis to evaluate macroeconomic trends and policy impact.

SQLD(SQL Developer)