Credit Data Analyst

Tanggung Jawab

Portfolio Monitoring: Analyze credit portfolio performance (NPLs, delinquency rates, vintage analysis, roll rates) and prepare periodic risk trend reports.

Data Exploration & Insight Generation: Conduct deep-dive analysis into customer behavior and credit data to identify risk patterns, anomalies, and opportunities.

Policy & Strategy Recommendations: Provide data-driven recommendations for adjustments to credit policies (e.g., cut-off scores, credit limits, pricing strategies).

Reporting & Dashboarding: Create, maintain, and automate dashboards using BI tools to monitor risk KPIs for stakeholders (Risk, Product, Business).

Cross-functional Collaboration: Support Risk Modelers/Data Scientists in the implementation and monitoring of credit scoring models.

Kualifikasi

Minimum bachelor’s degree in Statistics, Mathematics, Actuarial Science, Economics, Industrial Engineering, Computer Science, or another quantitative field.

Minimum 2 years of experience in Data Analytics, Risk Management, or Credit Scoring in the Banking, Fintech Lending, or Multifinance industries.

• Highly proficient in SQL (mandatory) for complex data manipulation, querying, and extraction.
• Familiarity with Python or R (especially libraries such as Pandas, Scikit-learn, and XGBoost).
• Proficient in creating dashboards using Superset, Tableau, PowerBI, or Metabase.Advanced level (VBA, Power Query, advanced Pivot Tables).
• Ability to translate complex data and numbers into actionable business strategies and risk policies.
• Strong problem-solving skills with a keen eye for detail and data anomalies.
• Ability to clearly explain data insights and risk trends to non-technical stakeholders.