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"I am a Computer Engineering student at Srinakharinwirot University specializing in Data Science, Machine Learning, and Data Engineering. I focus on developing production-grade pipelines, credit risk assessment systems, and transparent, explainable AI architectures tailored for the financial services industry."
- Education: B.Eng. in Computer Engineering, Faculty of Engineering, Srinakharinwirot University (SWU) (2022 – Present).
- Target Roles: Aspiring Data Scientist / Machine Learning Engineer seeking technical opportunities and internships within Banking, FinTech, and Risk Analytics.
- Core Domains: Credit Risk Modeling (Probability of Default, Long Overdue Debtor forecasting), Explainable AI (SHAP, LIME), Scalable Telemetry Pipelines, and Spatial ML Modeling.
- Problem Solving: Multi-competition hackathon finalist experienced in optimizing tabular prediction models under strict evaluation metrics (AUC) and production constraints.
- Languages: Thai (Native), English (Professional Working Proficiency, CEFR B1+ / Oxford Test Score: 51), and Japanese (Beginner).
| Issuing Organization | Assessment / Credential | Core Competencies & Score | Verification |
|---|---|---|---|
| SKILLKAMP by KBTG | Data Analyst Assessment (STAMP) | Score: 97/150 (Intermediate) -- Data Cleaning & Preprocessing (23/30), EDA & Visualization (20/30) | View Portfolio |
| SKILLKAMP by KBTG | Digital & Performance Marketer (STAMP) | Score: 98/150 (Intermediate) -- Digital Marketing Analytics (26/30), Data-Driven Marketing (21/30) | View Portfolio |
| AUA Language Center | Oxford Placement Test | CEFR B1+ (Score: 51/120) -- Use of English: 54, Listening: 48 | View Portfolio |
| Project | Domain / Core Focus | Tech Stack | Highlights |
|---|---|---|---|
| Credit Risk Scoring & Explainable AI | FinTech / Risk Analytics | Python, LightGBM, XGBoost, SHAP, OptBinning, FastAPI | Built Probability of Default (PD) scoring pipeline with regulatory-standard feature interpretability using SHAP attributions and monotonic WoE binning. |
| Manufacturing Telemetry & OEE Analytics | Industrial IoT / Data Engineering | Docker, PostgreSQL, Apache Spark, Airflow, SQLAlchemy, Streamlit | Architected high-frequency machine sensor simulator, automated batch ETL pipelines, and real-time OEE tracking. |
| GuardianAI - Frailty Risk Dashboard | HealthTech / Preventive Clinical AI | Python, XGBoost, FastAPI, React, SHAP | Deployed clinically interpretable screening system for elderly frailty attribution with low-latency API endpoints. |
| Long Overdue Debtor (LOD) Prediction | Financial Default Forecasting | Python, Pandas, Scikit-Learn, LightGBM, XGBoost | Engineered predictive models to classify 90+ day loan default risks on ~40,000 credit records, optimized for Area Under the ROC Curve (AUC). |
- Aihack Thailand 2025 (Final Round) -- Organized by AIRA & AIFUL, Chulalongkorn Business School (Dec 2025)
- Advanced through the Selection Round to compete as a national top 8 finalist in an intensive 3-day data science competition.
- Developed machine learning classification models on real-world financial loan datasets to predict Long Overdue Debtors (LOD, >90 days overdue after 12 months).
- Engineered predictive features, optimized pipeline performance for AUC leaderboard rankings across Public and Private test datasets on Probspace, and delivered strategic business insights.
- True Innovation Launchpad 2026 -- AI & Data Science Lead (Team Nakphatthana Tuapralat) (Jan 2026)
- Spearheaded data strategy and predictive modeling for elderly frailty prevention in the Healthcare Innovation Track, developing sub-30ms clinical risk scoring APIs.
- Geospatial Intelligence for Resilience Hackathon 2026 -- Spatial Data Scientist & ML Modeler (Jan 2026)
- Organized by GISTDA x KMITL x KMUTT; built "Rain-to-Flood" spatial model fusing Sentinel-1 SAR soil backscatter, Copernicus GLO-30 DEM, and precipitation APIs for 30m flash flood mapping.
- CDG Hackathon 2026 -- Team GrandGuardianAI (Jul 2026)
- Competed in architecting specialized AI solutions targeting high-impact public sector and operational challenges.
- LINE MAN Wongnai Junior Case Competition -- Strategic Growth & Unit Economics Lead (Team Low Cortisol) (Nov 2024)
- Formulated campus delivery optimization and "Silent Mission" growth campaign with 8.87 THB/user CAC, acquiring 462 VIP trial conversions.
Programming & Query Languages
Data Science & Machine Learning
Data Engineering & Infrastructure
Analytics, IDE & Productivity
