Job Description

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.

eFinancialCareers