Senior Manager: Validation and Quantitative Modeling

SUMMARY:
Our client in the Public Sector, has an opportunity available for a Senior Manager: Validation and Quantitative Modeling, to be based in the Sandton area.

POSITION INFO:
Requirements:

• An Honours degree or above in an advanced quantitative discipline such as Statistics /Mathematics/Econometrics/Finance/Applied Mathematics/Actuarial Science/Quantitative Risk Management/Engineering or equivalent professional qualifications in related disciplines
• Some certification in AI and/or ML application approaches will be advantageous
• Ten (10) years’ relevant work experience, with 2-3 years’ experience in finance or banking, specialising in modeling, financial or Asset liability management (ALM) risk management or in a similar role
• Three (3) years of experience with statistical modeling, R, Matlab, Python
• Two (2) years of experience with Java, SQL, data analysis libraries, analyzing datasets within relational databases, Hadoop or Spark and machine learning algorithms
• Knowledge of various regression techniques, parametric and non-parametric algorithms, times series techniques, and other statistical models, various model validation tests/methodologies
• Knowledge of validating various models built to assess and quantify broad financial risk, market risk, operational risk, interest rate risk, complex econometric capital, stress testing models as well as capital adequacy calculation is a plus
• Knowledge of Balance Sheet Risk Management advantageous
• Strong knowledge of capital market instruments and hedging strategies
• Strong knowledge in mathematical or statistical analysis and modelling techniques
• Experience in software development and financial modelling within a financial/treasury environment
• Experience in statistical modelling, model validation and model testing

• Conducting model validations on the Corporation’s models, both for in-house and 3rd Party developed models, based on regulatory guidance, internal policies and procedures and the industry’s leading practices
• Creating, validate, test, document, implement, and oversee usage of models for a variety of products and services used in the financial decision making process using a range of statistical, programming and database tools as C/C++, R, Python, Java, SQL, SAS, Hadoop, Spark
• Creating model development and/or validation documentation including presentations, written reports, model or reporting code documentation, business requirements, monitoring reports and related code and procedures
• Validating complex statistical models developed using new and emerging analytic tools/technologies such as Big Data, Artificial Intelligence (AI) and Machine Learning (ML)
• Formulating and periodically review the model validation charter and procedures and continually strive for efficiencies in the validation process

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