Senior Data Scientist - Credit Risk

We're seeking a driven and skilled Credit Risk Data Scientist 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.

Credit Risk Models:

• Develop, maintain, and monitor predictive models for credit scoring, fraud detection, and suspicious activity prediction.

• Write high-quality, production-ready code for models to be deployed in the production environment.

• Deploy models in the MLOps production environment, maintaining and troubleshooting any issues.

• Support regular model performance reviews, audits, and recalibrations.

• Leverage alternative data sources to enhance underwriting and credit risk models.

• Ensure alignment with model governance, business, and regulatory expectations.

Data Analytics to Help Business:

• Collect, process, and analyze data to support statistical analysis and risk decision-making.

• Design, implement, and maintain performance reports and actionable insights dashboards.

• Provide data-driven insights and develop dashboards to support loan approval processes and business decision-making.

• Conduct in-depth analyses to identify trends, patterns, and anomalies in lending data that can influence credit risk strategies.

• Present model concepts and metrics to senior stakeholders and validators/auditors.

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.