Data Scientist

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.

We are looking for a Data Scientist to develop data-driven solutions for credit risk assessment and decision-making. The role focuses on credit risk analytics, statistical modelling, algorithm development, and predictive modelling, working with financial and alternative data to improve credit assessment and risk strategies.

Job Description

• Develop, validate, and optimize credit risk and scoring models to support credit assessment and decision-making.
• Conduct credit risk analytics and exploratory data analysis to identify risk drivers, trends, and portfolio insights.
• Develop and enhance algorithms and predictive models for credit scoring, risk segmentation, and customer assessment.
• Perform feature engineering, variable selection, model development, and performance evaluation.
• Research and apply statistical, machine learning, and data mining methodologies to improve model performance.
• Conduct model validation, back-testing, stability analysis, and ongoing performance monitoring.
• Translate analytical findings into actionable risk and business recommendations.
• Work closely with Risk, Product, Business, and Data teams to develop data-driven credit strategies and solutions.

• Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Finance, or related quantitative fields.
• 4–5 years of experience in credit risk analytics, credit risk modelling, or data science, preferably within banking, multifinance, fintech lending, or financial institutions.
• Strong understanding of credit risk management, credit assessment, underwriting, and portfolio performance.
• Hands-on experience in developing credit scoring, risk models, or predictive models.
• Strong proficiency in Python and/or R, with solid SQL skills.
• Strong understanding of statistical and machine learning techniques, including logistic regression, decision trees, random forests, and other predictive modelling methods.
• Familiarity with credit risk metrics such as AUC/ROC, KS, Gini, PSI, bad rate, and approval rate.
• Experience supporting OJK audits, regulatory examinations, or regulatory-facing activities, including data preparation, documentation, and responding to regulatory inquiries, is a strong advantage.
• Experience working with financial, transactional, bureau, behavioral, or alternative data is an advantage.
• Strong analytical and problem-solving skills, with the ability to translate data into actionable insights.
• Good English communication skills and ability to collaborate across functions.