Credit Portfolio Risk Manager/Senior Manager

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, to empower all local businesses by creating an end-to-end food ecosystem through our channel LINE MAN and Wongnai. Connected consumers, riders, and local businesses and improved the daily life of all parties with restaurants nationwide. And because we are local, we provide the deepest variety and services that are tailor-made for Thai people.

Financial Products & Services team at LINE MAN Wongnai connects financially underserved customers on our platform, from small business merchants to delivery riders, with a span of financial services offerings, and is one of the fastest growing business units within LMWN.

With the power of a large-scale ecosystem, data, and technology, the in-house Fintech team helps Thai people live better and be more financially inclusive with uniquely innovative products and access to digital finance.

Responsibilities:

• Conduct deep-dive analyses, enhance monitoring tool, prepare report on the credit portfolio in terms of portfolio risk performance, customer risk profile, policy performance, and predicting risk patterns / trends.
• Provide suggestions to refine the credit decisioning and related policies / processes (e.g., underwriting, account / portfolio management, collection).
• Liaise with related stakeholders to formulate and execute the credit strategy / credit risk management guidelines, ensuring alignment with the company’s strategic objectives and risk appetite.
• Utilize data-driven insights / ML analytics to identify the targeted area for improvements and support in business growth opportunities.

Qualifications:

• Minimum 6 years of experience in portfolio risk management, credit risk analytics areas in banking or lending business with the focus on the retail credit risk. Experience in digital lending business / fintech is a plus.
• A degree in data science, financial engineering, statistics, risk management or related fields. Relevant professional qualifications (e.g., CFA, FRM, RAI) is a plus.
• Strong analytical and critical thinking skills with the ability to interpret extensive data and turn it into actionable strategies.
• Proficient in data analytics, data visualization tools (e.g, Python, advanced Excel, Power BI).
• Familiar in credit risk models concept / methodology (e.g., credit scoring, PD / LGD models, risk-based pricing) and ML analytics.
• Proficient in business-level English. Excellent verbal and written communication skills with the ability to present complex information clearly to diverse audiences.