Data Scientist - Risk Analytics & Modelling
Cermati.com Open · verified Oct 24, 2026 At a glance
Mid-level Data Science role at Cermati.com. Jakarta · full-time.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Track portfolio risk measures, flag unusual movements early and investigate what is driving deteriorating indicators
- Turn analysis into credit recommendations, then adjust risk controls when needed
- Build SQL features, analyses and dashboards that support ongoing portfolio monitoring
- Evaluate models occasionally to help improve credit scoring
What you bring
- A bachelor’s degree in a quantitative or analytical field, though other disciplines are also considered
- Practical use of Python, SQL and Excel for statistical work
- Strong analytical and problem-solving ability, with confidence exploring large tabular datasets and explaining findings
- Clear communication, teamwork and ownership, plus willingness to learn independently
Who this fits
You’ll suit work that combines hands-on data exploration with credit risk decisions and collaboration across business, product and engineering. The role is based onsite in Jakarta and is open to fresh graduates as well as candidates with experience.
From the employer
We're looking for candidates with strong analytical skills and hands-on experience working with financial datasets. You will be responsible for monitoring portfolio health, performing deep-dive exploration and analysis to identify risk drivers and improvements in our existing framework, and translating findings into actionable credit decisions. You will partner with business, product, and engineering teams to solve some of the most challenging problems in lending while also continuously improving portfolio quality by balancing risk control with growth opportunities. You will be embedded in a fast-paced environment, working within a strong team of data scientists with access to a robust data infrastructure.
Responsibilities
- Monitor portfolio risk metrics on a regular basis and proactively flag anomalies or emerging trends
- Perform root cause analysis when risk indicators deteriorate to pinpoint what's driving the change, such as identifying suspicious behavioral patterns
- Translate findings into concrete recommendations and implement adjustments as needed
- Build and maintain SQL-based features, analyses, and monitoring dashboards to support ongoing risk surveillance
- Perform occasional model evaluation to support credit scoring improvements
- Fresh Graduate/Bachelor's degree in an analytical or quantitative discipline (e.g. math, statistics, engineering, computer science), however other disciplines will be considered
- Experienced in using statistical computer languages such as Python, SQL, and MS Excel
- Have good communication skills and able to work together in a team
- Excellent problem-solving skills and have the drive to learn and master new technologies and techniques
- Willingness to learn new skills independently and have a strong sense of project ownership
- Not afraid to get your hands dirty exploring data, investigating anomalies, and building SQL-based analyses
- Comfortable working with large tabular datasets to detect trends and anomalies, and communicating findings as actionable recommendations.
- Exposure to credit scoring modelling concepts is a plus.
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