Data Analyst x3

The Data Analyst is responsible for contributing to the development and integration of approved Management Information System (MIS) dashboards and reports through analysing and transforming complex data, in line with company rules and regulations.

• Contribute to the development, implementation, and continuous improvement of data and analytics-related processes, procedures and operational plans, in line with departmental and company goals.
• Provide input into data requirements, model-design specifications and needs to support enhancement of operational efficiency within the Analytics team.
• Stay abreast of and provide technical advice and guidance on innovative Business Intelligence (BI) tools, trends and new visualisation technologies in the market to promote ongoing innovation.

• Collaborate with the Senior Business Intelligence (BI) Specialist and Analytics teams to execute assigned projects by integrating advanced analytical outputs into reporting deliverables.
• Develop, maintain, and enhance Management Information Systems (MIS) reports, dashboards, and analytical outputs in collaboration with relevant stakeholders, ensuring achievement of project deliverables and objectives.
• Analyse datasets to identify trends, anomalies, and performance insights that support business decision-making.
• Review data to ensure integrity reliability is maintained across systems, escalating and proposing corrective action / solutions for review and obtain approval by the Senior BI Specialist before implementation of corrective actions.
• Support integration and monitor performance of approved reporting and analytical solution implementation.
• Identify and elevate any risks or concerns to the Senior Specialist for review, while proposing and obtaining approval of solutions for implementation.
• Prepare and present analytical findings and visual outputs in business-relevant format, to inform decision-making.
• Recommend improvements to enhance reporting efficiency, data presentation, and information accessibility.

• Adhere to all data-governance and reporting standards in compliance with the Protection of Personal Information Act (POPIA), Financial Sector Conduct Authority (FSCA) requirements, and internal company policies, rules, and standards.
• Perform data-quality checks, validations, and reconciliations to maintain accuracy of reports and datasets.
• Maintain documentation of report structures, datasets, and data transformations in relevant data repositories to promote data hygiene, integrity, and reproducibility.
• Identify data risks, concerns, integrity issues, or compliance concerns to the Senior Business Intelligence (BI) Specialist for review and resolution.
• Support continuous improvement initiatives related to data quality, integrity, and governance frameworks.

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a relevant field (NQF Level
  7)
• Advanced degree or MBA preferred (Ideal)
• 3+ years of experience as a Data Analyst
• Experience in the Banking Industry (Advantageous))

A phased skills pathway for strengthening data engineering, business intelligence, predictive AI, automation, optimisation and strategic analytics capability.

• Data Pipeline Modernization: Database optimization, automated ETL pipelines and stored procedures.
• Advanced Business Intelligence: Advanced data modeling, context filtering, row-level security and cloud deployment.
• Enterprise Analytics Legacy Integration: Statistical profiling, macro migration and legacy predictive validation.

• Behavioral Modeling & Marketing AI: Binary classification and feature engineering for upsell/cross-sell propensity modeling.
• Lead Automation & Income Estimation: Regression trees, ensemble learning and automated lead generation scoring engines.
• Customer Service & Retention AI: Survival analysis, lifetime value estimation and NLP for service ticket intent.

• Spatial Network Optimization: Location allocation algorithms, spatial clustering and spatial regression.
• Marketing & Media Mix Optimization: Constrained optimization, attribution modeling and marketing mix modeling.
• Strategic Leadership & Architecture: Bridging deep technical capability with executive business decision-making and architecture patterns.