Deskripsi Pekerjaan
Join Direct Lending's innovative team as a Senior Data Scientist specializing in credit risk modelling. This pivotal role offers the opportunity to shape lending strategies through advanced analytics and predictive modeling. You'll work with unsecured consumer lending, Buy Now Pay Later (BNPL), and credit products to develop robust risk assessment frameworks that balance profitability and responsible lending.
Leverage your expertise to transform complex data into actionable insights that drive strategic decisions. Collaborate with cross-functional teams to design, validate, and deploy cutting-edge machine learning models. Your work will directly impact the company's risk tolerance, customer experience, and regulatory compliance efforts in Malaysia's dynamic financial landscape.
This position requires a strategic thinker who can navigate the intersection of data science and financial risk management. You'll stay ahead of industry trends while maintaining model accuracy and interpretability, ensuring our lending practices remain competitive and compliant with evolving regulations.
Tanggung Jawab
- Develop and implement credit risk models for unsecured consumer lending and BNPL products
- Analyze large-scale financial data to identify patterns and predict default probabilities
- Collaborate with business stakeholders to translate model insights into lending strategies
- Ensure regulatory compliance of risk models through rigorous validation and documentation
- Monitor model performance and recalibrate based on changing market conditions
- Present complex findings to senior leadership through clear visualizations and reports
- Lead initiatives to enhance data infrastructure for credit risk analytics
Kualifikasi
- 5-8 years of experience in data science with specialized focus on credit risk modelling
- Proven track record with unsecured consumer lending and BNPL credit products
- Expertise in machine learning algorithms (logistic regression, random forests, gradient boosting)
- Strong programming skills in Python/R with experience in financial data manipulation
- Knowledge of regulatory frameworks for credit risk management (Basel, etc.)
- Experience with cloud platforms (AWS/Azure) and big data technologies
- Master's degree in quantitative field (Statistics, Mathematics, Computer Science)