Shopee | Credit Risk Modeling Analyst
2 weeks ago
Experienced (Individual Contributor)
SeaMoney is a part of Sea Group, a leading global consumer internet company. SeaMoney’s mission is to better the lives of individuals and businesses in our region with financial services through technology. SeaMoney’s offerings include mobile wallet services, payment processing, credit offerings, and related digital financial services and products. These are available in seven markets across Southeast Asia and Taiwan under various brands, including ShopeePay, SPayLater, and other brands.
Job Description:
Design, develop, and implement risk models such as application / behavioral / collection (ABC) scorecards, Expected Credit Loss (ECL) models, Interest Rate Risk in the Banking Book (IRRBB) models, Liquidity Gap Report, stress test models, etc.
Utilize statistical and quantitative techniques, machine learning algorithms, and data analytics to enhance the predictive power and accuracy of risk models.
Conduct thorough data analysis to identify key variables and market trends that impact credit, market and liquidity risks.
Work closely with product managers and data owners to ensure the availability and quality of data required for model development.
Collaborate with product managers and IT teams to integrate models into the organization's systems and ensure seamless execution.
Perform ongoing validation and back-testing of risk models to ensure accuracy, relevance, and compliance with regulatory requirements.
Identify and address any issues or weaknesses in the models through continuous monitoring and improvement processes.
Prepare comprehensive documentation for risk models, methodologies, and validation processes.
Requirements:
Bachelor Degree or above in Finance, Computer Science, Statistics, Engineering, Economics or other relevant fields. Master's or Ph.D. in a quantitative field is preferred.
Relevant internship or full-time experiences on modeling within banking, financial services, financial technology or internet industry.
Proficiency in SQL and Python.
Experience with IFRS 9 accounting rules and ECL models is a plus.
Familiarity with machine learning techniques and statistical modeling is a plus.
Excellent analytical and problem-solving skills.
Knowledge of regulatory requirements related to risk modeling is a plus.
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