Job Summary
We are seeking a highly motivated Risk Analytics
Assistant Manager to join our Risk Analytics team within a consumer finance company.
This role is responsible for monitoring, analyzing, optimizing loan portfolio performance, developing and implementing credit risk models and supporting data driven decision making.
The position plays a key role in enhancing portfolio quality, strengthening risk management across lending products.
Key Roles & Responsibilities:
1. Portfolio Monitoring
- Develop and deliver regular reports and presentations materials relative to credit risk meeting.
- Build and maintain dashboards/reports to monitor key portfolio performance indicators such as approval rate, delinquency rate, roll rate and vintage analysis.
- Provide insight and recommendation to improve credit quality and portfolio performance.
2. Credit Risk Analysis
- Conduct ad-hoc analyses to identify risk trends and customer behavior patterns.
- Generate early warning signals and actionable insights on emerging risks.
- Perform A/B testing and evaluate the use of alternative data/scoring in credit decisioning.
- Assess the impact of credit policies changes on portfolio performance.
3. Data Management and Credit Risk Modeling
- Maintain and enhance credit risk data mart to support analytics and reporting.
- Perform feature engineering, enrich dataset for risk dashboards/modeling.
- Develop, validate, and implement, credit risk scorecards (application/behavior models).
- Monitor model performance, including discriminatory power, stability, and robustness.
- Conduct back-testing and UAT to support model deployment.
4. Cross-functional Collaboration
Collaborate with external partners & internal stakeholders to:
- Validate and implement decision engines and business rule engines (BRE).
- Enhance credit decisioning logic and automation process.
- Continuously improve operation efficiency and risk control.
1. Educational background
- Bachelor's degree in Finance, Economics, Statistics, Mathematics, Data Science, Management Information System, or a related quantitative discipline.
- Relevant certification (e.g., CFA, FRM, Data Analysis, Data Science) may also be considered.
2. Experience
- 3+ years of experience in risk analysis, risk modeling, data analysis or a similar role in the financial/fintech company.
- Knowledge of credit risk modeling and machine learning techniques.
3. Technical skills
- Strong programing skills (Python/R/SAS/SQL)
4. Soft skills
- Strong analytical and problem-solving skill.
- Business acumen with a risk management mindset.
- Ability to translate technical results into business.
- Good communication and stakeholder management.
- Ability to work independently with minimal supervision.
