Design and optimize data-driven credit related strategies for consumer and SME loans, including anti-fraud, collection, and risk policies.
Evaluate the creditworthiness of new applicants and monitor the life-time financial performance of existing customers.
Conduct data analysis on risk exposure and profitability to identify opportunities for product and strategy improvement. Provide credit risk insights and recommendations to internal teams and stakeholders.
Develop and track key indicators to detect fraudulent activities and optimize risk strategies to control the risk
Work with internal Product and Data Science team to ensure that the credit risk strategies are implemented accurately
Assess business operations and market trends to enhance competitive positioning.
Requirements
Bachelor's degree in Quantitative Finance, Statistics, Computer Science, Business Analytics, Data Science, or related fields.
Open to candidates across experience levels, including entry-level and experienced professionals.
Strong analytical skills and experience in data management.
Proficiency in SQL, Python, Excel, PPT.
Ability to navigate ambiguity, develop testable hypotheses, and drive actionable outcomes.
Strong attention to detail and ability to identify data inconsistencies.
Effective communication skills to present complex insights to technical and business stakeholders.
Prior experience in Retail/Institutional Banking, Consumer/SME Finance, Supply Chain Finance, e-Commerce, Consulting, or Credit Ratings is a plus.
