OM Bank - Credit Quantitative Analyst - Pinelands, Johannesburg Gauteng

Old Mutual is actively recruiting for a OM Bank - Credit Quantitative Analyst - Pinelands, Johannesburg position in Gauteng. This is an excellent opportunity for professionals in the Data / Business / Analysis / Ai sector looking to advance their careers.

• Experience Level: 2 - 5 years • Educational Background: Bachelor or equivalent • Industry Focus: Data / Business / Analysis / Ai • Location Preference: in Gauteng

The OM Bank - Credit Quantitative Analyst - Pinelands, Johannesburg position is an important role within the Data / Business / Analysis / Ai sector, offering meaningful career development and professional growth opportunities.

This role in Data / Business / Analysis / Ai offers valuable career progression opportunities aligned with your experience level and professional aspirations.

When applying for this OM Bank - Credit Quantitative Analyst - Pinelands, Johannesburg position, ensure your CV highlights: • Relevant experience matching the 2 - 5 years requirement • Educational qualifications in line with Bachelor • Specific achievements in the Data / Business / Analysis / Ai field • Any certifications or specialized training

The Data / Business / Analysis / Ai sector in South Africa continues to show strong demand for skilled professionals. This position represents a valuable opportunity in the current job market.

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At OM Bank, we strive to attract great people who are passionate about coming together for a higher purpose- building something unique and aspirational, always aiming to be the best they can be. We are rooted in our purpose to inspire and enable our customers to grow and sustain their prosperity. The Credit Quantitative Analyst is responsible for supporting credit risk analytics, portfolio monitoring, credit modelling, pricing analytics and reporting activities across the credit lifecycle. The role provides analytical support in the development, monitoring and enhancement of credit risk models and strategies covering origination, account management, portfolio performance and secured lending portfolios. The successful candidate will work closely with Credit Risk, Product, Finance, Collections and Business teams to provide data-driven insights that support responsible growth, sustainable profitability and effective risk management. While impairment and IFRS 9 exposure would be advantageous, the primary focus is on credit risk analytics, secured credit portfolios, originations, pricing, portfolio monitoring and model-driven decision-making

Credit Modelling & Portfolio Analytics

Support the development, monitoring and enhancement of credit risk models, scorecards and strategies. Analyse portfolio performance, customer behaviour and key credit risk trends. Perform model monitoring, back-testing and validation activities. Maintain appropriate model documentation and governance standards.

Credit Origination & Pricing Analytics

Support credit origination and decision strategy analytics. Analyse application, approval and booking performance across customer segments. Assist with risk-based pricing and profitability analysis. Provide insights to optimise growth, risk and customer outcomes.

Secured Credit Portfolio Management

Monitor the performance of secured lending portfolios, including Home Loans (HL) and Asset Vehicle and Asset Finance (AVAF). Analyse arrears, delinquency, default and recovery trends. Support portfolio reviews, policy assessments and performance monitoring. Contribute to stress testing and portfolio risk analysis.

Impairment & IFRS 9 Support (Advantageous)

Support impairment and IFRS 9 analysis where required. Assist with monitoring ECL, PD, EAD and LGD model outputs. Analyse impairment drivers and portfolio risk trends. Support model governance and documentation activities.

Reporting & Business Insights

Produce credit risk, portfolio and management reporting. Develop meaningful insights from large datasets and communicate findings clearly. Support dashboarding, reporting automation and process improvements. Identify emerging portfolio risks and opportunities.

Stakeholder Engagement & Governance

Work closely with Credit Risk, Finance, Product, Operations and Business teams. Present analytical findings to both technical and non-technical stakeholders. Support audit, governance and model review processes. Contribute to continuous improvement initiatives across risk analytics.

Skills & Experience (Required)

Bachelor's degree in Statistics, Mathematics, Actuarial Science, Economics, Finance, Data Science or a related quantitative discipline. 2–5 years' experience in credit risk, portfolio analytics, quantitative modelling or a related analytical role. Experience in credit risk, portfolio analytics, quantitative analysis or data analytics. Exposure to credit modelling, scorecards, pricing or originations analytics. Knowledge of secured lending products, particularly HL and AVAF, would be advantageous. IFRS 9 and impairment experience beneficial but not required. Strong analytical, problem-solving and communication skills. Experience using SQL, Python, SAS, R, Power BI or similar tools.

Technical

Credit risk modelling and portfolio analytics. Statistical and quantitative analysis techniques. Exposure to scorecard development, monitoring or validation. Data extraction, manipulation and analysis using SQL, Python, SAS, R or equivalent tools. Data visualisation and reporting using Power BI, Excel or similar technologies. Understanding of pricing, origination and portfolio performance metrics. Basic understanding of IFRS 9, PD, EAD and LGD concepts would be advantageous. Technical documentation and analytical reporting skills.

Leadership & Behavioural

Strategic thinking with strong commercial awareness Ability to influence senior stakeholders (Credit, Finance, Risk, Treasury) Strong judgement and control mindset Clear communication of complex risk topics Strong team leadership and talent development

Competencies

Strategic

Understands broader portfolio, customer and market trends. Demonstrates curiosity and commercial awareness when assessing business opportunities and risks.

Decision-Making Ability

Uses data and evidence to support recommendations. Applies sound judgement when analysing trends, risks and model outputs. Escalates risks, issues and anomalies appropriately.

Analytical & Risk Mindset

Strong numerical and analytical capability. Uses data to identify trends, opportunities and risks. Applies quantitative techniques to solve business and portfolio challenges. Demonstrates an appreciation for balancing risk, growth and profitability.

Collaboration (Relating)

Builds positive relationships across multiple teams and functions. Communicates analytical information effectively to technical and non-technical stakeholders. Works effectively within a team environment and contributes to shared goals.

Customer First

Supports responsible lending and sustainable customer outcomes. Considers the impact of analytical recommendations on customers and portfolio performance. Balances commercial objectives with prudent risk management.

Innovation (Perspective)

Demonstrates curiosity and continuous improvement thinking. Looks for opportunities to improve models, reporting and analytical processes. Embraces new methodologies, tools and technologies.

Personal Mastery (Learning)

Demonstrates resilience, adaptability and accountability. Actively seeks learning opportunities and feedback. Shows commitment to developing quantitative, technical and business skill.

Action Planning, Analytics Software, Budget Management, Business Intelligence (BI) Analysis, Computer Literacy, Data Analysis, Data Compilation, Data Controls, Data Interpretations, Data Modeling, Evaluating Information, Numerical Aptitude, Report Review, Solution Analysis, Statistical Analysis Techniques

Competencies

Business Insight Cultivates Innovation Manages Complexity Optimizes Work Processes Situational Adaptability Strategic Mindset

NQF Level 7 - Degree, Advance Diploma or Postgraduate Certificate or equivalent

27 August 2026 , 23:59