Technical Data Analyst at Nedbank

Job Purpose

• To design, develop, and maintain robust data systems that support credit risk analysis and decision-making processes.

Job Responsibilities

• Develop and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality.
• Interpret data, analyse results using statistical techniques, and provide ongoing reports.
• Identify, analyse, and interpret trends or patterns in complex data sets.
• Work closely with management to prioritize business and information needs.
• Locate and define new process improvement opportunities.
• Develop and maintain data governance frameworks to ensure data integrity and compliance with regulatory standards.
• Lead initiatives to enhance data security and privacy, ensuring all data handling practices meet industry best practices and legal requirements.
• Develop and maintain comprehensive documentation for all data processes and systems to ensure transparency and continuity.
• Conduct regular audits of data systems to identify and rectify any discrepancies or inefficiencies.

Essential Qualifications

• Minimum required Qualification: Bachelor’s degree in Computer Science / Mathematics / Financial Mathematics / Statistics/ Informatics/ Information Systems, or another quantitative field.
• Proven track record as a data developer or data analyst.
• Technical expertise regarding data models, database design development, data mining, and segmentation techniques.
• Strong knowledge of, and experience with reporting packages, databases (SQL, etc.), programming (ETL (Extract, Transform, Load) frameworks).
• Knowledge of statistics and experience using statistical packages for analysing datasets (Excel, Python, SAS, etc.).
• Certification in data management or analytics (e.g., Certified Analytics Professional, Microsoft Certified: Azure Data Scientist Associate etc.) would be advantageous.

Minimum Experience Level

• 3+ years’ experience in credit risk and data analytics
• Experience in data management and analysis, preferably within the credit risk environment.
• Familiarity with credit risk models and their implementation.
• Experience in handling large data sets and relational databases.
• Experience in leading cross-functional teams in data-driven projects.
• Proven / Demonstrable track record of business requirement implementation models /data models / rule set optimisation in a business environment.
• Experience in developing and implementing data quality frameworks.
• Knowledge of the Credit Banks Act Returns, Credit Risk Economic and Regulatory Capital, credit risk systems, data, and processes
• Background in data and financial risk management and understanding of credit risk assessment methodologies.