Credit Risk Data Scientist II

Coastal

WorldwideFully remoteFull TimeFinance & Banking
No salary statedPosted 3w ago

Why we think you can apply

Hiring model
Open worldwide · the employer states no country restriction
Work from
Anywhere, the UAE included

Posted 22 days ago

About the role

Responsibilities

  • Oversee the development, validation, and performance monitoring of credit risk models for decision-making and regulatory reporting
  • Apply expert-level data science and statistical techniques for loss forecasting and credit decisioning
  • Manage the model governance framework and ensure effective control processes
  • Conduct back testing and assess model performance to make necessary adjustments
  • Ensure alignment of modeling activities with the organization's risk appetite and strategic goals
  • Interact with senior management, auditors, and regulators regarding model performance

Requirements

  • 7+ years of experience in credit risk modeling, validation, or model risk management
  • Proven experience with Expected Loss (EL) using PD, LGD, and EAD frameworks
  • Deep expertise in machine learning and statistical techniques for CECL and CCAR
  • Proficiency in statistical software such as R, Python, SAS, and SQL
  • Strong knowledge of consumer credit, including credit cards and unsecured lending
  • Bachelor's degree in Quantitative Finance, Economics, Statistics, Mathematics, or Data Science

Preferred Qualifications

  • Master's degree in a quantitative discipline such as Financial Engineering or Applied Mathematics
  • Familiarity with credit scorecards and origination credit underwriting
  • Experience with Basel III, IFRS 9, and Dodd-Frank regulatory frameworks

Benefits

  • Comprehensive medical, dental, and vision insurance
  • 401(k) retirement plan with company matching
  • Health Savings Account (HSA) and Flexible Spending Accounts (FSA)
  • Generous paid time off and 11 paid holidays
  • Company-paid basic life insurance and disability coverage

About the Company

Coastal is a modern banking institution combining strong financial infrastructure with Banking-as-a-Service (BaaS) and fintech enablement strategies to empower individuals and businesses.

What we look for

  • Experience with PD, LGD, and EAD modeling framework
  • Expertise in machine learning and statistical techniques
  • Knowledge of CECL, CCAR, and stress testing
  • Proficiency in R, Python, SAS, or SQL
  • Understanding of Basel III and IFRS 9
  • Bachelor's degree in quantitative field
PythonRSASSQLMachine Learning
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