Job Description
Are you a fresh graduate with a passion for data and a knack for building predictive models? Dwi Cermat Indonesia is seeking a talented Data Scientist to join our Risk Platform team. In this role, you will leverage cutting-edge machine learning techniques to tackle credit risk challenges, driving smarter financial decisions and enabling safer lending practices.
You will work with large, complex datasets to uncover insights, develop risk scoring models, and deploy solutions that directly impact our business. As part of a collaborative and innovative team, you will have the opportunity to grow your skills while contributing to meaningful projects in the fintech space.
We value curiosity, analytical thinking, and a drive to solve real-world problems. If you are eager to apply your data science expertise in a dynamic environment, we want to hear from you.
Responsibilities
- Analyze large-scale transactional and behavioral datasets to identify credit risk patterns and trends.
- Develop, validate, and deploy machine learning models for credit risk scoring and fraud detection.
- Collaborate with product and engineering teams to embed models into the risk platform.
- Perform feature engineering and selection to improve model accuracy and interpretability.
- Monitor model performance in production and implement improvements as needed.
- Present findings and recommendations to cross-functional stakeholders including risk management and business leaders.
- Stay up-to-date with the latest research in machine learning and credit risk analytics.
- Contribute to the development of data pipelines and tools for efficient analysis.
Qualifications
- Fresh graduate or up to 1 year of experience in a data science or analytics role (internships included).
- Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
- Strong proficiency in Python and SQL for data manipulation and modeling.
- Hands-on experience with machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
- Understanding of statistical modeling techniques (regression, classification, clustering).
- Familiarity with credit risk concepts and financial products is a plus.
- Excellent problem-solving skills and ability to communicate complex ideas clearly.
- Self-motivated with a willingness to learn and adapt in a fast-paced environment.