Remote Credit Risk Analyst — Models & Portfolio Insight

Placements24

Gauteng

Hybrid

ZAR 420,000 - 660,000

Full time

3 days ago
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Benefits offered by this job

Health insurance
Remote work setup provided
Generous paid time off

Job summary

Placements24 is seeking a proactive Credit Risk Analyst for a fully remote role supporting operations nationwide in South Africa. You will assess borrower creditworthiness, develop statistical models for scoring and forecasting, and monitor portfolio risk to safeguard financial health.

The position requires strong quantitative skills, experience in credit risk analysis, and proficiency with SAS, R, and Python.

Qualifications

  • Bachelor's degree in Finance, Economics, Statistics, Mathematics, or related quantitative field.
  • Proven experience in credit risk analysis, preferably within banking/financial services.
  • Strong quantitative and analytical modeling skills; proficient in SAS, R, Python.

Responsibilities

  • Analyze credit applications, financial statements, and market data to assess borrower creditworthiness.
  • Develop, validate, and implement statistical models for credit scoring, loss forecasting, and portfolio risk management.
  • Monitor the performance of credit portfolios, identifying trends and potential areas of concern.
  • Formulate and recommend credit policies and procedures to manage risk effectively.
  • Prepare detailed reports on credit risk exposure, policy adherence, and portfolio quality for senior management.
  • Stay updated on regulatory changes and industry best practices in credit risk management.

Education

Bachelor's degree in Finance, Economics, Statistics, Mathematics, or a related quantitative field

Tools

SAS
R
Python

Job description

Placements24 is seeking a proactive Credit Risk Analyst for a fully remote role supporting operations nationwide in South Africa. You will assess borrower creditworthiness, develop statistical models for scoring and forecasting, and monitor portfolio risk to safeguard financial health.

The position requires strong quantitative skills, experience in credit risk analysis, and proficiency with SAS, R, and Python.

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