Credit Risk Data Scientist, Monee
Job Description
Job Description
- Build and deploy credit risk models (statistical, ML, deep learning) that directly determine who gets access to credit, your models will impact millions of lending decisions across consumer and SME products.
- Engineer features from massive-scale datasets spanning Shopee's e-commerce ecosystem, behavioral signals, and third-party financial data, turning raw data into a structured format that enhances model performance.
- Explore and apply Generative AI and Large Language Models (LLMs) to credit assessment, enhancing underwriting efficiency, and optimizing risk management processes.
- Conduct continuous data mining to generate actionable insights, supporting business decision-making and problem-solving.
- Own the full model lifecycle: development, validation, deployment, and performance monitoring in production.
- Bachelor's degree in Data Science, Artificial Intelligence, Machine Learning, Business Analytics, Information Technology, Finance, Economics, Statistics, Mathematics, or other related fields, expected to graduate by July 2027 and join us by Aug 2027.
- 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.
More Info
Key Skills
Gradient Boosting Models
Machine Learning Models
LightGBM
Generative AI
Feature Engineering
Large Language Models (LLMs)
About Company
Skills:
causal inference , Hadoop, Sql, Pytorch, Spark, Python, Machine Learning Algorithms, scikit-learn, transfer learning, reinforcement learning, multi-task learning, sequential modeling, graph learning
Skills:
MLops, Machine learning platforms, Data platforms, Backend systems, Data workflows, Feature engineering