Model Risk Management & Validation

PT Bank Neo Commerce Tbk; Jakarta Utara; On-site; IDR 500,000,000 - 800,000,000; Full time

Job summary

PT Bank Neo Commerce Tbk is seeking a senior Risk Analytics professional to independently validate credit risk models and monitor performance across application, behavioural, fraud, and collection domains. The role emphasizes robust validation, governance, and data-driven decision making in a fintech environment.

The ideal candidate brings 6–10+ years in risk analytics or data science, strong SQL and Python/R skills, and experience with alternative data sources to assess model drift and emerging

Qualifications

• 6–10+ years in Risk Analytics, Model Validation, Credit Risk Analytics or Data Science.
• Strong understanding of statistical modelling and validation techniques.
• Proficient in SQL; Python/R preferred.
• Experience in digital lending, consumer finance, fintech or digital banking.
• Strong analytical and communication skills.
• Experience with alternative data is preferred.

Responsibilities

• Independently validate all credit risk models (application, behavioral, fraud, collection, etc.).
• Design and execute model validation methodology including back-testing, stability, calibration and performance monitoring.
• Continuously monitor model performance and recommend recalibration or redevelopment.
• Explore, assess and onboard new internal and external alternative data sources.
• Conduct portfolio analytics to identify model drift and emerging risks.
• Develop model governance documentation and ensure regulatory compliance.
• Partner with Modelling, Business, Data and IT teams to improve model effectiveness.

Skills

Risk analytics

Model validation

Statistical modelling

Communication

SQL proficiency

Python/R

Tools

SQL

Python

R

Job description

Key Responsibilities:

• Independently validate all credit risk models (application, behavioral, fraud, collection, etc.).
• Design and execute model validation methodology including back-testing, stability, calibration and performance monitoring.
• Continuously monitor model performance and recommend recalibration or redevelopment.
• Explore, assess and onboard new internal and external alternative data sources.
• Conduct portfolio analytics to identify model drift and emerging risks.
• Develop model governance documentation and ensure regulatory compliance.
• Partner with Modelling, Business, Data and IT teams to improve model effectiveness.

Requirements:

• 6–10+ years in Risk Analytics, Model Validation, Credit Risk Analytics or Data Science.
• Strong understanding of statistical modelling and validation techniques.
• Proficient in SQL; Python/R preferred.
• Experience in digital lending, consumer finance, fintech or digital banking.
• Strong analytical and communication skills.
• Experience with alternative data is preferred.