Data Scientist, Credit Risk

Jobtailor; Philippines; On-site; PHP 1,200,000 - 2,000,000; Full time

Job summary

Jobtailor seeks a Credit Risk Modeler in the Philippines to build and improve Application and Behavioral scorecards for underwriting and collections decisions. You will work in a regulated environment, preparing documentation and defending modeling decisions to governance and BSP reviewers.

Collaborating with product, analytics, and engineering, you will drive model outputs into actionable strategy and production specs, covering data exploration through deployment and monitoring.

Qualifications

• 3+ years of hands-on experience building credit risk models (Application/Behavioral scorecards).
• Direct BSP exposure: participated in model audits or regulatory reviews.
• Strong Python (pandas, scikit-learn) and SQL.
• Experience across data, feature engineering, validation and production monitoring.

Responsibilities

• Build and improve Application and Behavioral scorecards used in underwriting and collections decisions.
• Prepare model documentation, support BSP audits, and defend modeling choices.
• Collaborate with product, analytics, and engineering to translate outputs into strategy and specs.
• Oversee full modeling cycle: data exploration, feature design, model build, validation, deployment, monitoring.

Skills

Credit Risk Modeling

Python Programming

SQL Proficiency

Scorecards

Tools

Databricks

Pandas

Scikit-learn

Job description

• Build and improve Application and Behavioral Scorecards that drive underwriting and collections decisions across live credit products
• Work within a regulated environment — prepare model documentation, support BSP audits, and defend modeling decisions to internal governance and external reviewers
• Collaborate with product, analytics, and engineering to translate model outputs into strategy changes and implementation specs
• Full modeling cycle: data exploration, feature design, model build, validation, deployment specs, and post-production monitoring
• Scorecard quality — tracked through AUC, KS, bad rate, stability index, and assessed against real portfolio outcomes via NPV and backtesting
• Model documentation and governance artifacts ready for regulatory review
• Credit strategy input — your models influence approval, pricing, and collection decisions, not just inform them

Requirements

• 3+ years of hands‑on experience building credit risk models (Application Scorecards and/or Behavioral Scorecards specifically)
• Direct BSP exposure: participated in model audits, prepared documentation, or supported regulatory review
• Strong Python (pandas, scikit-learn) and SQL
• Experience covering the full lifecycle: data, feature engineering, validation, production monitoring
• Familiarity with Databricks or similar environments is a plus

Core Competencies

Demonstrates expertise in building and validating credit risk models, particularly Application and Behavioral Scorecards, while ensuring compliance with regulatory standards. Proficient in translating model outputs into actionable strategies and collaborating across teams to enhance credit decision‑making processes.

Highest-signal resume keywords

• Credit Risk Modeling
• Python Programming
• SQL Proficiency
• Model Documentation
• Data Exploration

Hard Skills

• Credit Risk Models
• Application Scorecards
• Behavioral Scorecards
• Feature Engineering
• Model Validation
• Production Monitoring

Industry Keywords

• Regulated Environment
• Model Audits
• Governance Artifacts
• AUC
• KS
• Bad Rate
• Stability Index
• NPV
• Backtesting

Tools & Technologies

• Databricks
• Pandas
• Scikit-learn