Data Scientist (Lending)

• Develop and implement robust credit risk models (acquisition scorecards, behavioral scorecards, collection scorecards) for cash loan products to support the business.
• Investigate alternative data to improve the performance of the scorecard model beyond traditional credit data.
• Constantly monitor, enhance, and validate the models’ performance and conduct research on the latest modeling methodology and best industry practices, while complying with all regulatory requirements.
• Develop and keep up with enterprise risk management models, for instance, Basel, IFRS 9, PD, LGD, EAD models, stress testing, and macro-economic models.
• Carry out benchmarking/industry research to review regulatory requirement changes on RWA policies for better credit risk management.
• Capable of continuously identifying credit/business issues to find solutions or quality improvements using scoring/modeling/analytics tools.

Requirements

• Minimum of a Bachelor’s/Master’s degree with outstanding GPA in Math, Statistics, Computer Science, Risk Management, or Engineering.
• Minimum of 2+ years of experience in financial service data modeling, having deployed, built, and maintained such models in production using data modeling tools. A certification is advantageous.
• Experience with SQL, and Python programming (Python is compulsory), knowledge of Statistical/Machine learning algorithms 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 about retail/commercial loans of FI, credit risk and business process, and experience in doing data profiling, mapping attributes, ETL, and data governance.
• Attention to detail and a strong desire to do an excellent job and exceed expectations with the quality of your work in a fast-paced environment.
• Strong oral and written communication skills in both Indonesian and English, and the ability to explain terms to users.

Minimum skills:

• At least have built and productionized 1 credit scoring model
• Tools: Python, SQL language
• Ability to communicate in English