Senior Manager – Validation and Quantitative Modeling – Sandton –
R1 000 000pa – R1 300 000pa
Purpose of Post:
- 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.
Main Duties and Responsibilities:
- 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
- To undergo model validations at various stages:
- Pre-assessment: This applies to newly built-model assessment to ensure fit for purpose, compliance with policies and ensuring that the model documentation submitted is of a high- quality standard.
- Post implementation review (PIR): The PIR of newly developed model system, parameter update or calibration which is focused on ensuring correct implementation of the approved model and its
- Monitoring: The ongoing monitoring and validation of model performance to ensure the continued efficacy of models in use across the
- Out of cycle calibration: The periodic reviewed or recalibrated models to reflect changing economic and market conditions carried out during the
- Annual validation: The annual validation of models as per internal
- 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,
- 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
- 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
- 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
- Facilitating communication between the model validation team and stakeholders (i.e. model developers, model owners, users and internal/external parties) to ensure remediation of validation
- Formulating and periodically review the model validation charter and procedures and continually strive for efficiencies in the validation
- Contributing to the development and promotion of effective model governance process and validation practices within the
- Performing other ad hoc duties allocated by either the Head of ALM and Market Risk or ALCo from time-to-time.
- Preparing high-quality model appraisal reports and presentations to ALCo Technical Committee / ALCo / EXCo/
Knowledge, Skills and Personal Attributes:
- Excellent communication and report writing skills
- Ability to perform model validations at an accelerated pace without sacrificing quality
- Ability to clearly explain quantitative concepts to non-quantitative audience
- Self-starter who solves problems with little to no guidance
- Strong business and financial acumen
- Strong Project Management Skills
- Strong Analytical Skills
- Planning and Organizing
- Problem Solving
- Attention to detail
- Self-motivated and self-driven skills
- Coping with pressures and Setbacks
- Negotiating and influencing
- Interpersonal skills
Qualifications & Experience:
- 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
- Some certification in AI and/or ML application approaches will be
- Ten (10) years’ relevant work experience, with 2-3 years’ experience in finance or banking, specializing 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,
- Two (2) years of experience with Java, SQL, data analysis libraries, analyzing datasets within relational databases, Hadoop or Spark and machine learning
- 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
- Strong knowledge of capital market instruments and hedging
- Strong knowledge in mathematical or statistical analysis and modelling
- Experience in software development and financial modelling within a financial/treasury
- Experience in statistical modelling, model validation and model
Closing date for applications: 4 June 2021
Should you not hear from us within 14 days, please consider your applications unsucessful.
Desired Skills:
- statistical modeling
Desired Work Experience:
- More than 10 years
Desired Qualification Level:
- Honours