Assistant Manager / Manager

KPMG South Africa; Johannesburg; On-site; ZAR 600 000 - 1 000 000; Full time

Job summary

An established industry player is seeking a skilled Manager/Assistant Manager for their Credit Risk & Capital Management team. This role offers a unique opportunity to engage with complex statistical models and financial risk management. You will lead projects, develop credit risk models, and mentor junior staff while utilizing cutting-edge technologies. If you thrive in a dynamic environment and possess a strong quantitative background, this position is perfect for you. Join a collaborative team where your expertise will contribute to enhancing financial risk strategies for diverse clients, from local providers to major global banks. Your journey towards innovation and professional growth starts here.

Qualifications

• 5+ years of experience in quantitative credit risk roles.
• Strong knowledge of statistical techniques for credit risk modelling.

Responsibilities

• Develop and review credit risk models for provisioning and regulatory purposes.
• Manage projects through planning, execution, and close-out phases.

Skills

Quantitative analysis

Statistical techniques

Python

R

SAS

Project management

Team management

Communication skills

Education

Hons or Masters degree in Quantitative Finance

Degree in Mathematics or Statistics

Tools

Statistical software

Financial risk management models

Job description

Description Of The Role And Purpose Of The Job

We have an exciting opportunity to join our Financial Risk Management business unit, since we are looking to fill a Manager/Assistant Manager position in our Credit Risk & Capital Management team. We are a specialist function within KPMG’s Advisory Practice which has as its main purpose to assist clients with the development and review of often complex statistical models used to quantify financial risks. The Credit Risk & Capital management team is made up of credit risk modellers and analysts from a broad and diverse range of quantitative backgrounds, including mathematics, statistics, engineering and actuarial.

As a Manager/Assistant Manager, you will not only have a technical specialist role in the auditing and the development of credit risk models (IFRS9, scorecards, etc.), but also assist the Senior Manager with responsibilities with regard to the planning, organization and quality control of projects. The role offers exposure to a wide range of modelling techniques used by banks ranging from smaller local credit providers to globally systemically important banks. It also provides access to the latest technologies and developments, and you will be able to hone your coding skills in packages like Python, R and SAS.

Key Responsibilities

1. Development and review of credit risk models both for provisioning and regulatory capital requirement purposes.
2. Support with managing projects in the planning/budgeting, execution, and close-out phases.
3. Assisting with the coding and automation of financial risk management models.
4. Participating in building a coaching culture aimed at getting the best out of others in an environment where everyone in the team feels empowered to speak up or challenge where appropriate.

Skills And Attributes Required For The Role

1. Relevant experience within a quantitative credit risk-based role.
2. Well versed in contemporary statistical techniques and practices in credit risk modelling.
3. Able to read, interpret and create software code, and relevant experience with modern computing languages related to credit risk modelling (e.g. SAS, Python, or R).
4. Strong organisational and time management skills.
5. Proven track record of managing and delivering small workstreams.
6. Experience of managing teams, coaching and mentoring junior staff.
7. Able to work effectively in a fast-paced environment with conflicting priorities and deadlines.
8. Good presentation and communication skills with ability to articulate quantitative concepts to both technical and non-technical individuals.

Minimum requirements to apply for the role (including qualifications and experience):

1. A Hons or Masters degree in a quantitative discipline such as Quantitative Finance, Mathematics, Statistics or equivalent, FRM advantageous.
2. At least five years of experience in credit risk.