Credit Risk Data Scientist II

Coastal

Completely RemoteFull TimeFinance & Banking
Posted Today

Job description

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.

Skills & tools

PythonRSASSQLMachine Learning

What the team is looking for

Use this list as a quick fit check before you apply.

  1. 01Experience with PD, LGD, and EAD modeling framework
  2. 02Expertise in machine learning and statistical techniques
  3. 03Knowledge of CECL, CCAR, and stress testing
  4. 04Proficiency in R, Python, SAS, or SQL
  5. 05Understanding of Basel III and IFRS 9
  6. 06Bachelor's degree in quantitative field
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