Data Scientist - Risk Analytics & Credit Modelling

Cermati.com; Jakarta Pusat; On-site; IDR 180,000,000 - 260,000,000; Full time

Job summary

Cermati.com is seeking a data-focused risk analyst to monitor portfolio health and identify risk drivers. You will work with business, product, and engineering teams to translate findings into credit decisions.

You will build SQL-based analyses and dashboards to support ongoing risk surveillance in a fast-paced data science environment. Ideal candidates have a fresh or foundational degree in a quantitative field, strong Python/SQL/MS Excel skills, and a proactive, collaborative approach.

Qualifications

• Fresh Graduate/Bachelor's degree in an analytical or quantitative discipline.
• Proficient in Python, SQL, and MS Excel.
• Strong communication and teamwork abilities.
• Excellent problem-solving and quick learning.
• Willingness to learn new skills and take ownership of projects.
• Not afraid to explore data and run SQL-based analyses.
• Exposure to credit scoring concepts is a plus.

Responsibilities

• Monitor portfolio risk metrics and flag anomalies or trends.
• Perform root cause analysis to identify drivers of risk changes.
• Translate findings into actionable recommendations.
• Build and maintain SQL-based analyses and dashboards for risk surveillance.
• Support credit scoring improvements through model evaluation.

Skills

Data analysis

Statistical thinking

Communication

Teamwork

Problem solving

Education

Bachelor's degree (analytical/quantitative)

Tools

Python

SQL

MS Excel

Job description

Cermati.com is seeking a data-focused risk analyst to monitor portfolio health and identify risk drivers. You will work with business, product, and engineering teams to translate findings into credit decisions.

You will build SQL-based analyses and dashboards to support ongoing risk surveillance in a fast-paced data science environment. Ideal candidates have a fresh or foundational degree in a quantitative field, strong Python/SQL/MS Excel skills, and a proactive, collaborative approach.