About Us
We're seeking a driven and skilled Credit Risk Data Scientist (1 year contract) to join our dynamic team. If you're passionate about predictive modeling, risk management, and leveraging cutting-edge technologies, this role offers an exciting opportunity to contribute to the development of credit scoring and risk mitigation strategies.
Responsibilities
- Develop, maintain, and monitor predictive models for credit scoring, fraud detection, and suspicious activity prediction.
- Write high-quality production-ready code for the models that will be deployed in the production environment.
- Deploy the models in the MLOps production environment, and maintain and troubleshoot any production issues that arise with these models.
- Collaborate closely with Lending and Credit Risk teams to translate requirements into optimized models.
- Support regular model performance reviews, audits, and recalibrations.
- Collect, process, and analyze data to support statistical analysis and risk decision-making.
- Leverage alternative data sources to enhance underwriting and credit risk models.
- Present model concepts and metrics to senior stakeholders and validators/auditors.
- Design, implement, and maintain performance reports and actionable insights dashboards.
- Ensure alignment with model governance, business, and regulatory expectations.
Experience and Qualifications
- Degree (PhD, Master's, Bachelor's) in Statistics, Mathematics, Economics, Finance, Risk Management, or related field.
- Proven experience building risk models such as Application Score, Behavior Score, PD, EAD, LGD (Basel or IFRS 9), especially for retail customers in diverse countries including Singapore.
- Comprehensive understanding of risk management throughout the customer journey within fintech or risk-focused environments.
- Domain expertise in retail credit products, banking, and regulatory frameworks (Basel, IFRS).
- Proficiency in Python, R, SQL, Snowflake and Data Visualization tools like Tableau.
- Technical proficiency in data retrieval, data modeling, data mining, and predictive modeling.
- Strong familiarity with advanced machine learning techniques, statistical classification/regression for credit risk.
- Exceptional problem-solving skills, detail-oriented mindset, and ability to thrive in a dynamic work setting.
- Bonus: Familiarity with implementing models using Terraform scripts, Docker/Kubernetes, CI/CD technologies, AWS, or MLOps.
Why Join Us
- Make a significant impact on credit risk strategies and predictive modeling.
- Collaborative and innovative work environment.
- Opportunity to work with cutting-edge technologies and diverse datasets.
- Continuous learning and professional growth opportunities.
- Competitive compensation package and benefits.
