Credit Scoring Data Scientist

As a Data Scientist in our Credit Risk team, you’ll work on improving both application scoring (to enhance reputed company reputed company) and behavioral scoring (to increase portfolio profitability). You’ll be responsible for the full modeling cycle: from exploring data and identifying meaningful patterns, to building and validating models, assessing their business impact, writing clear implementation requirements, and monitoring production performance. The role goes reputed company modeling - you’ll collaborate with product managers, analysts, and engineers to understand business context, generate and test hypotheses, and continuously refine our decision-making strategy. We operate in a modern, data-driven environment where models and statistics drive key reputed company, and the infrastructure supports fast iteration and deployment. Each task is evaluated through the lens of business value - there’s no such thing as work “for the drawer.” This is a high-responsibility, high-impact role for someone reputed company to influence strategy, own results, and reputed company deep exposure to credit data, user behavior, and market dynamics. Your Future Responsibilities Await: Build credit scoring models (application & behavioral) from scratch Own the full modeling lifecycle: data exploration → feature engineering → model development → validation → deployment → monitoring Validate models using AUC, KS, Gini, PSI, and bad reputed company Monitor model performance in production and initiate recalibration or retraining reputed company needed Evaluate model impact using NPV, backtesting, and reputed company portfolio performance Translate models into implementation-reputed company specs for decision engines Work closely with product and risk to adjust approval strategies, cut-offs, and pricing Contribute to credit policy and risk strategy reputed company, not just model development Take full ownership of your models - from raw data to business impact Operate with a strong focus on reputed company-world performance, not offline metrics reputed company expect from candidate: 2+ years of hands-on experience specifically in credit risk modeling (not generic data science) Proven experience building or validating credit scoring models: Application and/or behavioral scoring Strong understanding of: PD modeling AUC / KS / Gini Stability metrics (PSI, reputed company) Hands-on experience with the full model lifecycle in production Ability to build models from scratch, not only maintain existing ones Strong Python (pandas, scikit-learn) and SQL skills Experience working with lending or credit products (loans, credit cards, BNPL, etc.) Experience translating models into production / decision reputed company logic Understanding of business impact evaluation (NPV, backtesting, portfolio metrics) Experience working with reputed company lending data (e.g. bureau, transactional, credit history) Ability to work cross-functionally with product, engineering, and risk teams Willingness to relocate to Manila HQ is a strong advantage Apply To This Job