Summary
Data Scientist with hands-on experience in credit risk modeling, decision systems, and machine learning pipelines. Skilled in transforming complex analytical models into business-driven insights. Experienced in Probability of Default (PD) modeling, OCR systems, and end-to-end ML deployment.
Education
Chulalongkorn UniversityExpected May 2026
B.Sc. in Computer Science
Work Experience
AI Engineer Intern | ClickNext Co., Ltd.Jan 2026 - Present
- Fine-tuned an OCR model (Surya) for Thai handwriting recognition, reducing Character Error Rate (CER) from 60.95% to 19.98% (−67%), significantly improving accuracy for real-world document processing.
- Developed a computer vision and automatic speech recognition pipeline to extract structured numerical data from live broadcast feeds.
- Collaborated with cross-functional teams to deliver ML solutions aligned with business requirements.
Project
Video Anomaly Detection System using SlowFast and Adaptive MissionGNNAug 2025 - Mar 2026
- Built a scalable multi-GPU feature extraction pipeline using SlowFast R50 (temporal dynamics) and ImageBind (visual semantics), generating high-dimensional fused representations (3,328 features) from surveillance video data.
- Enhanced the MissionGNN architecture by introducing a learnable projection layer to align fused features with a knowledge graph embedding space, enabling structured anomaly reasoning.
- Developed a weakly supervised training framework using decaying thresholds and anomaly-aware loss functions, achieving mAUC 0.8376 on the UCF-Crime dataset.
Risk-Adjusted Return Optimization Framework (Credit Risk Modeling)Jan 2026 - Feb 2026
- Built an end-to-end credit risk modeling pipeline, including data cleaning, feature engineering, and exploratory analysis on lending datasets.
- Developed a Probability of Default (PD) model using XGBoost with monotonic constraints aligned with financial risk logic.
- Applied isotonic regression calibration to ensure reliable and interpretable risk scores.
- Designed and optimized a credit decision engine by tuning Probability of Default (PD) thresholds, achieving $1.11M economic profit, 24.66% RAROC, and 56.3% approval rate at an optimal 9% PD threshold, under Basel III constraints.
- Translated model outputs into business visualizations (risk vs. return, PD thresholds) to support lending strategy decisions.
Multi-Label Emotion Detection in Tweets (BERTweetMA)Jan 2025 - Feb 2025
- Built a multi-label classification model using BERTweet with attention mechanisms on 38K tweets.
- Designed emotion-specific attention blocks with sigmoid-based classification.
- Achieved: F1-micro 0.728 | F1-macro 0.689 | Jaccard 0.699.
Task Tracking Web ApplicationMar 2024 - Aug 2025
- Designed and developed a role based task management system for project tracking and cross-team collaboration.
- Led frontend development and UX/UI design using NextJS to improve usability and workflow clarity.
- Architected system structure including task status, role permissions, and project hierarchy to ensure scalable and maintainable design.
Technical Skills
- Programming Language: Python, SQL, TypeScript
- ML & Data: NumPy, Scikit-learn, TensorFlow, OpenCV, XGBoost
- Data & Systems: Data pipelines, model calibration, feature engineering
- Web Framework: React, Next.js