About You
- You're a go-getter with mad juggling skills (or multiple hats) who can thrive in a fast-paced, agile environment
- You enjoy doing purpose-led and meaningful work
- You have a strong thirst for knowledge and are driven to find solutions that don't exist yet
- You are comfortable with ambiguity and extremely resourceful (in your past life, you could've been a detective)
- You always find a way to get things done without sacrificing the quality of your work, integrity, and values
- No task is off limits for you
- You are humble and prioritize the success of the team over your own with an eagerness to help those around you
- You don't shy away from challenges and can bounce back from setbacks
- We strongly encourage individuals with disabilities to apply. We believe in equal opportunity and strive to create an inclusive workplace where everyone can thrive.
What you'll do and what success looks like in this role:
- Extract and prepare datasets from BigQuery and other relevant data sources to support portfolio analysis, modeling, and team reporting requirements.
- Support the Manager, Credit Risk Analytics in preparing daily and monthly portfolio monitoring reports, including analysis of FPD (First Payment Default), NPL (Non-Performing Loan), CoC (Cost of Credit), and vintage/cohort metrics.
- Assist in analyzing portfolio trends and credit portfolio segmentation using leading and lagging indicators to identify risk areas that require further attention.
- Support the Manager, Credit Risk Modelling in the development and maintenance of IFRS 9-based ECL (Expected Credit Loss) / provision models, including input data preparation, assumption validation, and methodology documentation.
- Assist in the periodic provision calculation process (monthly/quarterly) by ensuring data accuracy and consistency of the parameters used in accordance with applicable policies.
- Support the execution of regulatory (OJK) and internal stress testing by preparing scenario data, developing model input tables, and assisting in the interpretation of simulation results under Mild, Adverse, and Severe scenarios.
- Assist in the development and validation of credit scorecards by preparing sample data, analyzing variable distributions, and conducting statistical model performance testing.
- Support the performance analysis of external models and third-party credit scores through periodic monitoring of KS (Kolmogorov-Smirnov), Gini, and population stability metrics.
- Conduct ad hoc data analysis based on the needs of the Team Lead and team, including creating data visualizations and dashboards in Looker Studio to support management reporting and presentations to the Board of Commissioners.
- Document analytical processes, assumptions, and findings in a clear, organized, and systematic manner to serve as reference materials for the team.
What Is Required and What We're Looking For
- Final-year students or fresh graduates in Statistics, Mathematics, Actuarial Science, Finance, Information Technology, or other related quantitative disciplines.
- Strong analytical and quantitative skills, with experience working with large-scale data and a solid understanding of basic statistical concepts such as distributions, regression, and correlation.
- Proficient or familiar with SQL for data extraction and analysis; experience with Python is considered a plus.
- Familiar with data visualization tools such as Looker Studio, Tableau, or Power BI.
- Basic understanding of credit risk, the credit lifecycle (origination, underwriting, collection), and ECL/IFRS 9 provisioning concepts is an advantage.
- Detail-oriented, well-organized, and highly attentive to accuracy, particularly in data validation and analytical documentation processes.
- Able to work collaboratively in cross-functional teams (analytics, modeling, and systems) and communicate analytical findings clearly and effectively.
- Interested in the digital banking or fintech industry.
- Proficient in both Indonesian and English, with strong verbal and written communication skills.
