Quantitative Analyst at Nedbank

Job Purpose

• To contribute to the development and maintenance of best practice models and assessment strategies in line with regulations (where applicable) in order to facilitate world class risk management.
• Model Risk Assurance plays a pivotal role in the validation, assurance and governance of non-regulatory risk models, ensuring the accuracy and reliability of the bank’s non-regulatory risk models and processes, thereby safeguarding the integrity of the banks risk management framework.

Job Responsibilities

• The role provides in-depth exposure to the bank’s non-regulatory models. The work will be focused on models across the bank (i.e both retail and corporate banking). This involves:
• Performing validation of material non-regulatory models, which includes some of the following models:
• Credit acquisition(i.e origination models) and pricing
• Anti-money laundering (AML)
• Application fraud 
• Collections
• Operational Risk
• Climate risk (fossil fuel ratios, carbon accounting and stress scenarios) and 
• Macro-economic models 
• Providing thought leadership and guidance on model methodology and design, assisting to optimise the banks non-regulatory models.
• The role offers high visibility across the organization as analyses and reports will be tabled at technical forums, board level committees, as well as to the bank’s internal and external auditors, hence the analyst will be required to interact with senior stakeholders on a regular basis. 
• The ideal candidate will blend excellent communication, report writing, project management and general banking knowledge with solid technical expertise. The analyst will be required to provide constructive challenge to business and recommend improvements to models as a subject matter technical expert.
• Developing challenger models, building business and product knowledge, researching best practice methodology, as well as automation of role related tasks are key components of this role.
• The divisional culture emphasizes development, especially of leadership and behavioural skills, as well as embracing psychological safety. The team will focus on Machine Learning, Artificial Intelligence (AI), Automation and expansion into new areas. This provides opportunities for development and establishing an organisation wide reputation for the ambitious candidate.

Deliverables:

• Validation of non-regulatory models – This includes quantitative and qualitative validation of the models, the governance as well as the data, together with the application thereof.
• Subject matter expert - Provide input/assistance in the build and refinement of relevant models.
• Model replication and reperformance - Independent development of models to assess potential for improvement on existing ones.
• Challenger models – Independently develop challenger models, to help better understand strengths and shortcomings of “current in use” models.
• Model Assurance – Ensuring that calculations as well as model outputs, reports and associated commentary are accurate, reliable and fit for their intended purposes.
• Continuous learning - Keeping abreast with industry best practice as well as cutting edge modelling techniques in order to fulfil the role as a subject matter expert. Conduct research into model development and validation best practice. 
• Liaising with the stakeholders - Liaising with the business, Credit, as well as senior modelers to ensure that the validation process and feedback are optimised. Preparing and presenting reports to senior management.
• Change facilitation - Facilitate improvement in risk models and processes.
• Organizational learning - Knowledge sharing, research and mentoring of junior staff members and graduates, including skill transfer.
• Documentation - Document work performed and findings of validations. Prepare balanced and objective written communications to various stakeholders, including SARB, the external auditors of the bank and the Board.
• Ad-hoc - Assisting management with various ad‐hoc tasks, reports, specific deep dives, knowledge shares and analysis.

Essential Qualifications - NQF Level

• Advanced Diplomas/National 1st Degrees

Preferred Qualification

• Honours degree in Statistics/Mathematics/Econometrics/Computer Science/Finance/Actuarial Science or related quantitative discipline

Minimum Experience Level

• 1+ years’ experience in risk, quantitative or treasury modelling, validation environment – with a strong preference for programming in python.

Technical Exposure

• Knowledge of legislative requirements for regulatory credit capital models under the AIRB approach 
• Statistical or mathematical modelling skills  
• Knowledge of IFRS 9 Financial Instruments standard for the calculation of credit impairments is an advantage  
• Understanding of credit modelling and rating process  
• MS Office, particularly Excel (advanced user)  
• SAS and VBA