Apply on company website Bangkok, TH On-site Full-time

LINE MAN Wongnai is hiring a Senior/Lead Data Scientist (Credit Risk)

About LINE MAN Wongnai LINE MAN Wongnai is Thailand’s Leading On-Demand Delivery and Lifestyle e-Commerce platform services. We build technology to help Thai people live better. We empower all local businesses by creating an end-to-end ecosystem through our channel LINE MAN and Wongnai to connect and improve the daily life of consumers, riders, and local businesses nationwide. And because we are local, we provide the deepest variety and services that are tailor-made for Thai people. We are looking for an experienced Data Scientist to lead the science behind our Financial Products & Services operations. This role focuses on building and scaling data-driven risk systems that balance growth and profitability. Success in this role requires strong credit risk and modeling expertise, sound risk judgment, and excellent communication skills to align technical recommendations with business, product, and risk stakeholders. What you’ll Do: Credit Risk Modeling & Measurement - Develop, implement, and maintain core credit risk models, including application scorecards, behavioral models, and PD / LGD / EAD estimation frameworks. - Leverage diverse data sources—transactional, behavioral, financial, sequential and alternative unstructured data—for feature engineering and model innovation. - Own ECL measurement and monitoring, ensuring models accurately reflect portfolio risk across products, cohorts, and vintages. - Design robust model evaluation, back-testing, and recalibration processes to maintain performance under changing borrower behavior and market conditions. - Quantify and manage trade-offs between disbursement growth, risk appetite, and profitability. Experimentation - Design and analyze controlled experiments or policy tests (e.g., limit changes, approval threshold adjustments) to measure causal impact on risk and profitability. - Ensure changes to credit policies are supported by rigorous evidence and clearly understood risk implications. Cross-Functional Collaboration - Partner closely with the business team, product, engineering, accounting and operations to align modeling outputs with operational constraints and business objectives. - Support model governance, documentation, and audit requirements, including alignment with internal risk frameworks and regulatory expectations What you’ll Need: - Bachelor Degree in Computer Science, Statistics, Quantitative Finance, Economics, or related fields - 5+ years of experience in data science, credit risk, or quantitative modeling; experience in BNPL, consumer lending, or fintech is strongly preferred. - Strong understanding of PD, ECL, and portfolio risk concepts, with the ability to visualize and translate them into practical business decisions. - Strong Python and SQL skills. - Great communication skills, organization skills, multitasking and teamwork. - Good command of English and Thai
Job Details
Location Bangkok, TH
Work mode On-site
Employment Full-time
Department Data and Analytics
Category Data & ML
Posted 8 months ago
Application On company website
About company
LINE MAN Wongnai

LINE MAN Wongnai is one of Thailand’s largest tech companies, uniting LINE MAN, Wongnai, and LINE Pay to digitalize Thailand and empower users and businesses nationwide. The company connects people, riders, local businesses, and consumers through its platforms to create better living for all.

It operates as a leading on-demand services and restaurant information platform in Thailand, offering services such as food delivery, local business discovery, and digital payments. The company supports small businesses and street vendors by providing technological infrastructure, data insights, and digital tools to help them grow and thrive.

LINE MAN Wongnai is committed to driving Thailand's digital economy forward through innovation, sustainability, and public-private collaboration, exemplified by initiatives like supporting the Hawker Center Lumpini and promoting digital transformation for SMEs.

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