2 дня назад
Junior Data Scientist (Risk Analytics & Modelling)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Junior Data Scientist (Risk Analytics & Modelling) (Python/SQL): Monitoring lending portfolio health, investigating risk drivers, and translating data findings into actionable credit decisions with an accent on anomaly detection, SQL-based analysis, and credit risk modelling. Focus on performing root cause analysis, building monitoring dashboards, and evaluating models to improve credit scoring while balancing risk control with portfolio growth.
Location: Jakarta, Indonesia
Company
operates in the lending and financial services domain, using data-driven solutions to manage credit risk and improve portfolio quality.
What you will do
- Monitor portfolio risk metrics and proactively identify anomalies and emerging trends.
- Perform root cause analysis to investigate deteriorating risk indicators and suspicious behavioral patterns.
- Translate analytical findings into credit recommendations and implement framework adjustments.
- Build and maintain SQL-based features, analyses, and monitoring dashboards.
- Evaluate models to support improvements in credit scoring.
- Collaborate with business, product, engineering, and data science teams on lending risk challenges.
Requirements
- Fresh graduate or bachelor's degree in mathematics, statistics, engineering, computer science, or another analytical discipline.
- Hands-on experience with Python, SQL, and Microsoft Excel.
- Ability to work with large tabular financial datasets to detect trends and anomalies.
- Strong analytical, problem-solving, communication, and teamwork skills.
- Willingness to learn independently, master new technologies, and take ownership of projects.
- Comfort investigating data anomalies and communicating findings as actionable recommendations.
Nice to have
- Exposure to credit scoring modelling concepts.
Culture & Benefits
- Full-time employment in a fast-paced environment.
- Work within a strong data science team.
- Access to robust data infrastructure.
- Collaborate across business, product, and engineering functions.
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