Senior Data Scientist

2 days ago

Singapore GXS Bank Full time

Overview

We are 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.

Responsibilities
  • 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.
  • 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.
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.
Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Analyst, Information Technology, and Other
  • Industries: Banking and Financial Services
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