Careers at Capitec Bank

Purpose Statement

• Under the guidance of the respective investigations manager, investigate instances of risk related to various types of fraud incidents (e.g. claims fraud for Capitec Insurance. This will include internal fraud, serious breach of policies and procedures, and criminal syndicates). Investigate the matter, the parties involved and provide appropriate evidence for disciplinary hearings and/or criminal proceedings. Identify control weaknesses and recommend preventative measures, improvements, and training initiatives against potential fraud.

Experience
Min:

• 3 plus years’ experience as a Forensic Investigator/Auditor 

Ideal: 

• Proven experience as a Forensic Investigator/Auditor in the Financial Services Sector

Qualifications (Minimum)

• A relevant tertiary qualification in Forensics

Knowledge
Min:

• Investigation methods and procedures  
• Criminal law and law of evidence of the judicial process

Ideal: 

• Fraud and misrepresentation in the insurance industry

Skills

• Analytical Skills
• Communications Skills
• Computer Literacy (MS Word, MS Excel, MS Outlook)
• Decision making skills
• Interpersonal & Relationship management Skills
• Negotiation skills
• Presentation Skills
• Reporting Skills

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About the role:

• As Manager: Data Analytics at Capitec Business Banking, you will deliver data-driven solutions, identifybusiness opportunities, and use analytics and predictive models to enhance decision-making. You willturn strategic plans into actionable insights and promote best practices. By encouraging collaboration and using advanced solutions, you will help strengthen Capitec'sleadership in analytics and data-driven insights.

Our ideal candidate has:

• Over ten years of experience in a commercial setting, including four years in a team leadership ormanagerial capacity. Ideally with a proven track record of delivering value through data-drivendecision-making.
• Proficient in SQL and delivering complex analytical requirements.
• Managing senior and executive level stakeholders and influencing decision making at these levels
• Experience with cloud platforms (AWS).
• Experience with low/no code AutoML tools like Power BI or AWS Sagemaker.
• Data visualisation with tools such as PowerBI
• Big data frameworks – Hadoop/Kafka
• Github experience or Git

Soft Skills:

• Analytical and problem-solving skills.
• Excellent communication and interpersonal skills.
• Strong facilitation and presentation abilities.
• Commercial and strategic thinking skills.
• Attention to detail and accuracy.
• Ability to drive innovation and simplify processes.

Education:

• Completed a Bachelor's Degree in Commerce, Engineering, Mathematics, or Statistics.

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Purpose Statement

• To improve client experience within the Business Support Centre by ensuring operational readiness for change, leveraging data insights to drive continuous improvement, and reinforcing effective governance across service environments.

Experience
Min:

• 3–4 years’ experience in a servicing or fast-paced operational environment
• Exposure to operations environment and/or operational reporting environments
• Experience using Microsoft Excel (at least intermediate level)
• Demonstrated ability to analyse operational data, identify trends, and support improvement initiatives

Ideal:

• Exposure to analytical responsibilities, including interpreting data and providing actionable insights
• Proven ability to contribute to or support continuous improvement and operational change initiatives

Qualifications (Ideal or Preferred)

• Bachelor's Degree in Business Management

Knowledge
Min: 

• The business environment in the context of service providers.
• Client Engagement and Support policies and procedures
• Operational support: dialler software, including technical knowledge of business support systems
• Understanding of client experience principles and best practices. 

Ideal: 

• Understanding of Capitec Bank's internal environment and processes
• Debt collection processes | Credit Risk Management | Retail Credit Industry
• National Credit Act (NCA)
• Regulations relating to predictive diallers
• Contact centre software tools
• Technical knowledge of telecom hardware
• Exposure to project coordination and tracking deliverables.
• Cloud service knowledge on platforms such as AWS connect and Salesforce

Skills

• Analytical Skills
• Attention to Detail
• Communications Skills
• Computer Literacy (MS Word, MS Excel, MS Outlook)
• Decision making skills
• Interpersonal & Relationship management Skills
• Numerical Reasoning skills
• Planning, organising and coordination skills
• Problem solving skills
• Reporting Skills

Conditions of Employment

• Clear criminal and credit record

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What You’ll be Doing

• Develop and integrate .NET-based solutions for new and existing finance products. 
• Support app development (Java experience beneficial) and ensure seamless integration with data environments and third-party platforms. 
• Build and maintain AWS pipelines, including EC2, Lambda, and containerization (Kafka experience preferred). 
• Operate independently in a lean team, delivering high-quality solutions with minimal supervision. 
• Collaborate with diverse partner teams and adapt communication style to suit different stakeholders. 

What We’re Looking For

• 3+ years’ proven experience in both front- and back-end software development, project delivery and implementation
• Experience with modern front-end and back-end frameworks and technologies
• Integration skills with data environments and third-party APIs. 
• Ability to work across multiple platforms and environments. 
• Must be able to operate independently without extensive hand-holding or development plans.
• Strong communication skills and adaptability are essential

Tech Stack:

• Strong proficiency in .NET (C#);
• Java experience is advantageous. 
• AWS experience (EC2, Lambda, pipeline development, containerization, Kafka).
• Kubernetes 
• Kafka
• Terraform
• AWS Certification - desirable

Education (Minimum)

• Grade 12 National Certificate / Vocational

Education (Ideal or Preferred)

• A relevant tertiary qualification in Information Technology

Skills

• Analytical Skills
• Attention to Detail
• Communications Skills
• Interpersonal & Relationship management Skills
• Problem solving skills

Additional Information

• Clear criminal and credit record

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• We’re looking for a senior Machine Learning and Data Science Analyst to independently validate high‑impact models across credit risk, financial crime, and advanced analytics use cases. 
• This is a hands‑on technical role.

What You'll Be Doing
Leading the independent validation of machine learning models across: 

• Credit risk models
• Propensity and behavioural models
• Financial crime models (fraud and AML)
• Applying advanced ML techniques, including: 
• Supervised learning (Random Forest, XGBoost, CatBoost, Neural Networks)
• Unsupervised learning (clustering, isolation forests)
• Managing model risk across the end‑to‑end model lifecycle, including: 
• Feature engineering and data preparation
• Model training, evaluation, and selection
• Production deployment and monitoring
• Building and reviewing models in Python‑based environments 
• Leading and mentoring analysts and junior data scientists 
• Partnering closely with Risk, Technology, and Business stakeholders 
• Ensuring models meet governance, performance, and scalability standards

What We Are Looking For

• 6–8+ years relevant experience, with demonstrated technical leadership  
• Strong hands‑on experience building machine learning and data science models end‑to‑end 
• Proven use of techniques such as:  
• Boosting algorithms (XGBoost, CatBoost) 
• Neural networks 
• Clustering and anomaly detection 
• Advanced proficiency in Python 
• Solid experience with SQL and working with large, complex datasets 
• Ability to lead technically while remaining actively involved in modelling work 
• Experience within credit risk, propensity modelling, or financial crime analytics 
• Experience with independent validation of models and/or detailed peer review 
• Proven experience researching machine learning models 

Qualifications

• Honours or Master’s degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative field 

Preferred/ Ideal

• Experience leading or building ML teams in a regulated environment 
• Experience deploying or supporting models in cloud environments 
• Exposure to credit risk modelling, scorecards, or IFRS‑related analytics 
• Financial crime (fraud or AML) modelling experience 
• Experience designing models with scalability and deployment in mind 
• Familiarity with model risk, governance, or validation standards