Credit Risk Analyst Modelling
- Recruiter
- eSmart Recruitment
- Location
- Sandown, South Africa
- Salary
- Competitive salary
- Posted
- 25 Oct 2019
- Closes
- 24 Nov 2019
- Ref
- 2340085
- Job role
- Accountant
- Sector
- Accounting - Public practice
Our client in the banking institutions is seeking a Credit Risk Analyst Modelling that will join their Home Loans Department or Collections Department. The position is based in Sandton.
Minimum requirements:
- Bsc/ Bcom in Statistics, Mathematics, Applied Science, Quantitative Management, Actuarial science
- 3 - 5 years credit risk modelling
- Must have experience with SAS, SQL, Excel, Python
- Scoring and bad debt provision techniques in consumer lending
- Credit risk analysis on unsecured lending products
- Preparing data-driven credit policy recommendations for Senior Management and delivering compelling presentations
- Experience/exposure to bureau data and developing customer insights from it
- Manipulating and analysing data using SAS, SQL, SAS Macros or other tools for complex modelling purposes / forecasting (ability to perform statistical analysis on large datasets)
- Database architecture, i.e. understanding of database and data warehouse
Responsibilities:
- Undertake analysis to determine the impact of strategy changes to areas of application and account management strategies
- Development of predictive models aimed at the optimisation of risk decision-making
- Present ideas via reports and presentations, outlining findings and making recommendations
- Investigate data integrity issues, test assumptions and validate analytical results, ensuring accuracy and sensitivity of findings
- Use advanced analytical techniques (modern data mining, pattern matching, data visualisation and predictive modelling tools to produce analyses and algorithms that assist with the business decisions
- Use data-oriented approach to work with others in solving complex business problems around profitability, marketing, risk, and operational analysis
- Build additional models that can assist advance business and key situations that require models
- Analyse contemplated changes to credit models and review the actual performance vs expectation to inform business decisions
- Ensure variances to the expected model results are reported, reviewed, fully understood and used to enhance business performance
For more information please contact Koketso (contact number), alternatively email your updated CV to (email address)
Minimum requirements:
- Bsc/ Bcom in Statistics, Mathematics, Applied Science, Quantitative Management, Actuarial science
- 3 - 5 years credit risk modelling
- Must have experience with SAS, SQL, Excel, Python
- Scoring and bad debt provision techniques in consumer lending
- Credit risk analysis on unsecured lending products
- Preparing data-driven credit policy recommendations for Senior Management and delivering compelling presentations
- Experience/exposure to bureau data and developing customer insights from it
- Manipulating and analysing data using SAS, SQL, SAS Macros or other tools for complex modelling purposes / forecasting (ability to perform statistical analysis on large datasets)
- Database architecture, i.e. understanding of database and data warehouse
Responsibilities:
- Undertake analysis to determine the impact of strategy changes to areas of application and account management strategies
- Development of predictive models aimed at the optimisation of risk decision-making
- Present ideas via reports and presentations, outlining findings and making recommendations
- Investigate data integrity issues, test assumptions and validate analytical results, ensuring accuracy and sensitivity of findings
- Use advanced analytical techniques (modern data mining, pattern matching, data visualisation and predictive modelling tools to produce analyses and algorithms that assist with the business decisions
- Use data-oriented approach to work with others in solving complex business problems around profitability, marketing, risk, and operational analysis
- Build additional models that can assist advance business and key situations that require models
- Analyse contemplated changes to credit models and review the actual performance vs expectation to inform business decisions
- Ensure variances to the expected model results are reported, reviewed, fully understood and used to enhance business performance
For more information please contact Koketso (contact number), alternatively email your updated CV to (email address)