Data Scientist - Johannesburg North, South Africa - Communicate Recruitment
Description
Opportunities available for a talented Data Scientist with experience in predictive modelling and scorecards to join our team.Job & Company Description:
My clients are continuously on the lookout for dynamic individuals to form part of their teams that will aim to innovate and revolutionize their sector by designing, implementing and improving data analytic techniques, processes and state of the art mathematical models that will assist in identifying new business opportunities, offer solutions to existing and future challenges and help implement advanced business strategies.
As a Data Scientist, you will be expected to use your skills and expertise to develop and maintain predictive models and scorecards to support our credit risk management initiatives.
You will also work collaboratively with our risk management and analytics teams to design, develop and implement analytical solutions that drive business growth and profitability.
Education:
- BSc Computer Science, Mathematics, Statistics, Engineering, Econometrics, Physics or Actuarial Degree
- Honours Degree will be advantageous
Job Experience & Skills Required:
- 3+ years of experience in predictive modelling and scorecard development in the Banking industry
- Strong knowledge of statistical methods and tools such as SAS, R, or Python
- Experience in model development (such as scorecards, impairments and predictive modelling)
- Experience with data visualization tools such as Tableau or Power BI
- Machine learning or stress testing will be an added bonus
Quantitative Risk
- Retail & Wholesale Credit Risk
- Model Development (PD, LGD, EAD)
- IFRS 9 implementations
- Model Validation & Model Risk
- Pricing & Profitability
- Economic Capital Modelling
- Credit Risk Acquisitions & Collections
- Decision Analytics
Actuarial
- Pricing & Product Development
- Valuations
- SAM / Solvency II
- IFRS 17
For more information contact:
Daniël le Grange
Recruitment Specialist:
Actuarial and Quantitative Risk
For more information please contact:
Daniel le Grange
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