Senior Manager: Validation and Quantitative Modeling

SUMMARY:
To perform validation tests, discussing findings with internal and external stakeholders, writing validation reports, managing model risk across the Corporation as well as ongoing monitoring of models used in financial decision-making process

POSITION INFO:

JOB DESCRIPTION

• Developing tools/programs leveraging multiple programming languages to automate and enhance the reports and activities as well as routine independent review/evaluation of quantitative analytics and complex modeling projects
• 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 applications and user interface for routine tasks as well as provide quantitative tools, analysis and general day-to-day quantitative support in terms of model building, testing and implementation;
• 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, test, document usage and ensure the systematic review and on-going assessment of new/existing models to assess fit for purpose, conceptual soundness, mathematical theory and construct, data/assumptions, and output reasonableness;
• Validating complex statistical models developed using new and emerging analytic tools/technologies such as Big Data, Artificial Intelligence (AI) and Machine Learning (ML); 
• Ensuring all models are accurately inventoried and properly documented and liaise with 3rd Party model validators;

JOB REQUIREMENT

Qualifications:

• 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. 
• Moreover, some certification in AI and/or ML application approaches will be advantageous.

Selection Criteria

• 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; and
• Experience in statistical modelling, model validation and model testing.

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