Model Validation at Kiatnakin Phatra Bank (2024-07 – Present)
- Performed end-to-end validation of AI/ML models, including predictive (income forecasting, probability of default) and segmentation models, as well as credit risk models (IFRS 9, credit scoring, decision models), covering data validation, model implementation, and ongoing performance monitoring.
- Evaluated model performance using advanced techniques (backtesting, benchmarking, sensitivity analysis) to ensure robustness and stability from both statistical and business perspectives.
- Conducted research and analysis on diverse data sources to identify predictive signals and support model validation and performance improvement
- Identified model risks (bias, overfitting, data shift issues) and implemented actionable improvements, such as data quality monitoring, to strengthen model robustness and alignment with business needs.
- Collaborated with model development teams across multiple functions (customer & digital, credit risk, data science, and portfolio management) to ensure compliance with Model Risk Management (MRM) frameworks and regulatory standards.
Credit Risk Management – Portfolio Management at Kiatnakin Phatra Bank (2024-03 – 2024-07)
- Analyzed auto loan portfolio data to generate insights and support underwriting decisions and loan policy adjustments. Developed and refined credit risk policies, criteria, and underwriting guidelines for auto finance products.
- end-to-end process of managing risk for individual borrowers, starting from customer acquisition and data collection, followed by credit assessment using scoring models and underwriting policies to approve and price loans.
- Monitored portfolio risk and built risk indicators, including early warning signals, to support proactive risk management.
- Supported data preparation and reporting for portfolio quality review and decision-making
Data Engineer at HAUP Co. Ltd. (2023-07 – 2024-03)
- Created and maintained optimal data pipeline architecture. Assembled large, complex datasets meeting functional and non-functional business requirements for teams.
- Extracted, transformed, and loaded (ETL) data from a wide variety of sources such as MySQL, MongoDB, and Firebase databases using SQL and Python.
- Built analytics tools that utilized the data pipeline to provide actionable insights into customer acquisition. Designed databases for new products and built dashboards for teams.
- Collaborated with stakeholders, including Executive, Product, Data, and Software teams, to assist with data-related technical issues and support their data infrastructure needs.
Data Scientist/Quantitative Intern at Pi Securities (2023-03 – 2023-05)
- Researched and developed quantitative analysis in the stock market. Implemented time series forecasting techniques and designed trading strategies for profit using machine learning and quantitative methods.
AI/Data Scientist Intern at Ztrus (2022-04 – 2022-11)
- Developed an OCR and information extraction engine, utilizing PyThaiNLP for Thai text processing, performing data preprocessing (JSON, CSV), building confidence scoring to improve accuracy, and conducting UAT before deployment to end users.
