Job Description
Are you a passionate data professional eager to shape the future of financial services? Dwi Cermat Indonesia is looking for a talented Data Scientist to join our Risk Platform team. In this pivotal role, you will be at the forefront of credit innovation, leveraging complex datasets to build robust statistical models that drive financial inclusion and risk mitigation.
You will work closely with our engineering and product teams to refine credit risk assessment frameworks, optimize decision-making engines, and translate raw data into actionable business intelligence. We are seeking a candidate who thrives in a fast-paced environment and possesses a deep curiosity for machine learning applications in the fintech landscape.
This position offers the opportunity to tackle real-world financial challenges while working with a collaborative team dedicated to excellence. If you have a solid grasp of statistics, a knack for programming, and a drive to solve high-impact problems, we want to hear from you.
Responsibilities
- Develop, test, and deploy advanced statistical and machine learning models to assess credit risk.
- Analyze large-scale structured and unstructured datasets to uncover trends, anomalies, and insights.
- Collaborate with cross-functional teams to integrate data models into the existing risk management platform.
- Conduct A/B testing and model validation to ensure accuracy and regulatory compliance.
- Monitor model performance and implement improvements to mitigate financial exposure.
- Present data-driven findings and technical strategies to stakeholders to support business growth.
- Document data workflows, model architectures, and technical requirements.
Qualifications
- Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
- Fresh graduates with relevant internship experience or project portfolios are encouraged to apply.
- Strong proficiency in programming languages such as Python or R.
- Solid understanding of statistical modeling, probability, and machine learning algorithms (e.g., Logistic Regression, Decision Trees, XGBoost).
- Experience with SQL for database querying and data extraction.
- Familiarity with data visualization tools (e.g., Tableau, Power BI, or Matplotlib/Seaborn).
- Excellent analytical, problem-solving, and communication skills.