We're seeking a Credit Risk Manager to shape our ML-driven underwriting strategy and strengthen our risk decisioning globally. In this role, you'll combine analytical depth with hands-on model development to drive smarter, fairer decisions. From monitoring portfolio health to designing and deploying robust credit risk models, you'll help us balance growth with prudent risk management. Working closely with data, engineering, and product teams, you'll turn insights into business impact and improve approval funnels, refining policies, and expanding access to credit responsibly. In this role, you'll combine analytical depth with hands-on model development to drive smarter, fairer decisions.
Responsibilities
- Monitor key risk metrics (e.g., default rates, approval rates) and investigate significant changes.
- Analyze large datasets to identify trends, anomalies, and areas for improvement in risk management processes.
- Simulate the impact of credit policy or model changes, support A/B tests, and help guide rollouts to improve approval funnel performance.
- Track performance post-implementation and refine strategies using feedback loops and business KPIs.
- Develop, test, and deploy risk models in an iterative, agile manner.
- Monitor the performance of risk models, tracking feature stability, accuracy, and drift over time.
- Understand country-specific factors such as onboarding processes, customer limit management, and local alternative data sources.
- Collaborate with internal and external data vendors to evaluate and integrate new data sources.
- Contribute to the setup of early warning signals for portfolio deterioration, using a mix of quantitative and qualitative data.
Qualifications
- At least 5 years of experience in consumer credit risk analysis
- Bachelor's degree in business, finance, economics, actuarial studies, computer science or another relevant field
Required Skills
- Demonstrated proficiency in consumer credit risk assessment and how it relates to other business units (marketing, engineering, finance, and legal)
- Hands-on experience building, testing, deploying, and monitoring credit risk models (e.g., logistic regression, XGBoost, scorecards)
- Good statistical and mathematical skills
- Good working knowledge of SQL and Python
- Strong written and verbal communication skills in English
- Able to communicate complex credit risk concepts clearly to non-technical stakeholders
- Independent, creative, and proactive problem-solving mindset
Preferred Skills
- Previous experience in a fintech, neobank, or digital lending environment
- Able to design and deploy data marts and alerts
- Familiarity with credit data sources or regulatory environments in Southeast Asia (e.g., Thailand, Philippines, Indonesia)
- Previous experience with cloud platforms, AWS and GCP
- Experience in the design and automation of credit portfolios or financial reports
- Familiar with model deployment frameworks like Flask/FastAPI or MLflow
- Familiarity with MLOps tooling (e.g., Airflow, dbt, or feature stores)
Pay range and compensation package
A competitive salary and benefits package
Equal Opportunity Statement
We are committed to diversity and inclusivity.
