Data Scientist (Lending) di Moladin

Develop and implement robust credit risk models (acquisition scorecards, behavioral scorecards, collection scorecards) for cash loan products to support business.
Explore alternative data to enhance the scorecard model performance on top of traditional credit data.
Continuously monitor, improve, and validate the models’ performance and research on the latest modeling methodology and best industry practices, while meeting all regulatory requirements.
Develop and maintain enterprise risk management models e.g. Basel, IFRS 9, PD, LGD, EAD models, stress testing, and macro-economic models.
Conduct benchmarking/industry research to review regulatory requirement changes on RWA policies for managing better credit risk.
Able to keep identifying the credit/business issues to find solutions or quality improvements using scoring/modeling/analytics tools.

At least a Bachelor’s/master’s degree with excellent GPA in Math, Statistic, Computer Science, Risk Management or Engineering.
Min. 2+ years experience in financial service data modeling that have deployed, build, and maintained such models in production using data modeling tools. Certification is a plus.
Experience of SQL, and Python programming (Phyton is mandatory), knowledge of Statistical/Machine learning algorithm such as Logistic Regression, and Gradient boost (XGBoost/CatBoost), KMeans.
Mathematical, modeling, and reasoning skills to understand Credit Scoring/Propensity models and deploy them accurately and use that to make actionable recommendations.
Knowledge in retail / commercial loans of FI, credit risk and business process and experience in doing data profiling, mapping attributes, ETL, and data governance.
Care about doing an excellent job and exceeding expectations with the quality of what you do in fast paced environment.
Solid oral and written Indonesian and English communication skills and able to communicate terms to users.

Minimum skills:

Data Scientist (Lending)