Data Scientist

Who We Are

PT Credit Bureau Indonesia (CBI), as one of the private credit bureaus in Indonesia has been established since 2014 and obtained an operational license from Otoritas Jasa Keuangan (OJK) as Lembaga Pengelola Informasi Perkreditan (LPIP) in 2015.

In November 2021, after obtaining approval from OJK, CBI received additional capital from shareholders and appointed a new management team, which aims to provide new and leading-edge services and products. This new identity will also strengthen CBI's position as the best-in-class, modern and innovative credit bureau in Indonesia.

CBI is a trailblazer in the credit bureau industry, dedicated to fostering a culture of excellence and innovation. We believe in the power of a talented and diverse team to bring cutting-edge solutions to our clients and contribute to the overall success of the financial landscape in Indonesia.

Why Join Us

• Innovative Environment: Continuously investing in cutting-edge technologies, including the powerful realm of artificial intelligence, your role becomes a pivotal part of our journey into the dynamic and evolving landscape of financial services. Being part of our innovative environment is your gateway to an exciting and forward-thinking career
• Impactful Work: We offer more than just a job; we provide an opportunity to play a crucial role in shaping the financial future of individuals and businesses across the nation. As a licensed credit bureau, our commitment to accuracy, reliability, and timeliness sets the stage for impactful work
• Professional Development: We are committed to the growth of our employees. Join a team that encourages continuous learning and offers opportunities for career advancement.
• Collaborative Culture: Work in a collaborative and inclusive environment where your ideas are valued, and teamwork is key to achieving our goals.
  
  

Role Overview

We are looking for a Data Scientist to build and maintain the credit risk models behind our credit scoring products. You will own the full modeling cycle, from data analysis and feature engineering to model development, validation, and monitoring, using large-scale credit data in a data-sensitive financial environment. Candidates who can also strengthen the technical foundations of our modeling work, such as ML pipelines, model deployment, and code management, will have a strong advantage.

Job Responsibilities

• Develop, validate, and maintain credit scoring and credit risk models, covering sample design, feature engineering, model training, evaluation, and documentation.
• Analyze large-scale credit data to find predictive signals and support business needs.
• Monitor model performance and stability after deployment, and recommend recalibration or redevelopment when needed.
• Research and apply new modeling methods and data-mining techniques to improve model performance.
• Present modeling results clearly to both technical and non-technical stakeholders.
• Contribute to the team's modeling infrastructure, including feature pipelines, model deployment, and code standards.
  
  

Job Requirements

• Bachelor's degree or above in Statistics, Mathematics, Data Science, Computer Science, or a related field.
• 3–5 years of professional experience in data science, including hands-on credit risk or credit scoring model development.
• Strong understanding of credit risk concepts, such as probability of default, scorecard development, model validation, and performance metrics like AUC, KS, Gini, and PSI.
• Solid knowledge of common machine learning algorithms, such as logistic regression, decision trees, gradient boosting, and neural networks.
• Proficiency in Python and SQL, with experience working on large datasets.
• Good written and verbal English communication skills, with the ability to work well across functions.
  
  

Nice to Have

• Experience building or maintaining ML platforms, such as feature management, model training pipelines, model serving, and monitoring.
• Strong engineering skills, including Linux environments, Git, and database design.
• Experience implementing AI Agent applications.