Key Responsibilities
1. Data Analysis & Reporting
- Build, automate, and maintain dashboards for business KPIs (loan disbursal, portfolio quality, collections, conversion funnel, customer behavior).
- Conduct deep-dive portfolio analysis on risk, vintage curves, and credit performance across products and cohorts.
- Use Excel (Advanced Functions,Pivot, Power Query, VBA, scenario analysis) and SQL for day-to-day analytics and reporting.
2. Risk & Credit Analytics
- Support the development of credit policies by analysing applicant and borrower performance.
- Build scorecards and risk models in collaboration with the credit and product teams.
- Monitor delinquency, roll rates, provisioning requirements, and recommend corrective actions.
3. Predictive Modelling & ML
- Apply advanced ML techniques (Python/R, scikit-learn, XGBoost, TensorFlow, etc.) for risk scoring, fraud detection, and early warning systems.
- Build and test predictive models to optimize lead scoring, cross-sell opportunities, and collection strategies.
4. Business Partnering
- Work with cross-functional teams (Product, Credit-Ops, Growth, Finance) to translate data insights into strategic decisions.
- Present findings clearly to senior management with actionable recommendations.
Requirements
- Bachelor's or master's degree in Statistics, Mathematics, Economics, Computer Science, or related field.
- Excellent communication and presentation skills in English and Bahasa.
- 2–3 years in data analytics roles, mandatorily in
consumer lending fintech, banking, or credit risk
- Advanced
Excel
(Pivots, Macros, VBA, What-if Analysis, Solver, Dashboards)
- Experience with
BI tools
(Power BI, Tableau, Looker, or similar)..
- Strong
SQL
(complex queries, optimization, stored procedures).
- Hands-on with
Python/R
for data analysis and machine learning.