Credit Risk Data Scientist - Monee (2026 Graduate)
MoneeSingapore1 day ago
Full-timeEngineering, Information Technology
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Job Description
- Develop credit risk models to accurately assess user credit worthiness, supporting the expansion of Retail Finance and SME Finance businesses.
- Identify fraudulent behaviors from large-scale user data and build models to detect anomalies and mitigate fraud risks.
- Develop and maintain a feature pool consisting of both Shopee ecosystem data and third-party data, extracting valuable insights from massive datasets. Utilize statistical methods and machine learning techniques to transform raw data into a structured format that enhances model performance.
- Explore and apply deep learning and Generative AI in credit assessment to improve risk detection, enhance underwriting efficiency, and optimize risk management processes.
- Build and maintain graph databases, and explore the applications of graph-based models in risk management.
- Conduct continuous data mining to generate actionable insights, supporting business decision-making and problem-solving.
- Open to fresh graduates who are expected to graduate by July 2026
- Bachelor’s degree in Data Science, Artificial Intelligence, Machine Learning, Business Analytics, Information Technology, Finance, Economics, Statistics, Mathematics, or other related fields.
- Strong understanding and hands-on experience with Machine Learning Models (Logistic Regression, Random Forest, Gradient Boosting Models - XGBoost / LightGBM etc.) and feature engineering techniques.
- Solid statistical knowledge and strong data analysis abilities, with the capability to identify problems from data and develop data-driven solutions.
- Proficiency in SQL and Python is mandatory, with experience in PySpark as a plus.
- Strong passion and curiosity for credit business, risk management, and data analytics.
- Experience in network analysis, search and recommendation systems, or other machine learning fields is a plus.
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