Business Intelligence Analyst (Generative AI) at Capitec Bank

Purpose Statement

• Apply business process reengineering and data analytics experience to support and manage the optimisation of Generative AI solutions through Retrieval-Augmented Generation (RAG) workflows. This involves integrating various data sources, refining prompts, and continually enhancing AI retrieval accuracy to improve both product performance and user experience. 
• Drive measurable value for the product line by leveraging data and Generative AI tools to address client and business challenges, improve decision-making, and enhance product effectiveness. Use data analysis and business intelligence skills to generate actionable insights that support faster, more informed decisions and increase engagement with Generative AI products. 

What you will do:
Ownership and Responsibility for Allocated Area

• Own and manage the allocated product, focus or client area by maintaining Generative AI and data product quality, coordinating with product and content owners, and ensuring accurate, consistent and up-to-date source content. Plan and organise day-to-day work based on team direction and priorities, using sound judgment in routine decisions while escalating complex or unusual issues. Build a solid understanding of the business domain, collaborate with more experienced Business Intelligence Analysts and cross-functional teams, and actively contribute to a culture of data-driven decision-making.

Deliver on Business Requirements

• Use appropriate tools, methodologies and platforms to understand business needs, clarify the value to be derived from data and Generative AI, and translate these into clearly documented requirements with realistic timelines. Extract, combine and manipulate data from multiple sources to answer business questions, applying a methodical approach to problem solving within own scope. Engage constructively with stakeholders by providing overviews of requirements, prioritising tasks, estimating impact and risk, and delivering end-to-end, data-driven analysis that identifies key business triggers, assesses their effect on reports and KPIs, and is communicated in a clear, timely and professional manner.

Deliver Data Insights

• Create and share meaningful data visualisations, reports and analytical outputs that address core business questions and support decision-making. Use storytelling principles in visualisations to highlight key insights relevant to the problem statement, ensuring all outputs adhere to internal standards and methodologies. Communicate insights in a structured, stakeholder-appropriate way so that findings are easily understood and actionable.

Knowledge Sharing, Standards and Data Quality

• Actively develop own skills and knowledge, especially in Generative AI and its application in data and analytics, while maintaining strong housekeeping through regular review and clean-up of work. Follow analytics best practices to support continuity, optimisation and high data quality, and assist in establishing effective processes for query resolution. Participate in Communities of Practice to share knowledge, refine standards and adopt emerging AI-driven approaches, staying up to date with industry trends in BI, data warehousing, BI architecture, Generative AI and related technologies.

Education (Minimum)

• A relevant tertiary qualification in Business Administration or Mathematics

Knowledge and Experience
Minimum:-

Knowledge

• At least 1 years’ experience as Business Intelligence Analyst or equivalent (data analyst etc.) including experience in data analytics, BI methods and tools, data warehousing and the data life cycle
• Experience in identifying, quantifying, and subsequently delivering value on how to solve business challenges using data
• Exposure of using data transformation and visualisation tools such as Power BI, SQL, Python and Excel
• Experience in building data visualisations using tools such as Power BI
• Design thinking
• The Data Product Life Cycle (DPLC)
• Fundamental knowledge of data privacy and security regulations
• Fundamental knowledge of data quality and incident management  

Experience:

• At least 1 years’ experience as Business Intelligence Analyst or equivalent (data analyst etc.) including experience in data analytics, BI methods  and tools, data warehousing and the data life cycle
• Experience in identifying, quantifying, and subsequently delivering value on how to solve business challenges using data 
• Exposure of using data transformation and visualisation tools such as Power BI, SQL and Excel
• Experience in building data visualisations using tools such as Power BI

Ideal:

• Knowledge of and experience operating on the AWS (or similar) data stack
• Experience in building data visualisations using tools such as Power Bi Knowledge of agile project management methodology
• Knowledge and experience with Copilot in Microsoft 365: understanding integrations in Excel, Power BI, Word, Outlook, and Teams.
• Knowledge and experience with Copilot Studio: fundamentals of building conversational agents.
• Knowledge and experience with prompt design within Copilot: using natural-language instructions to query enterprise data, generate narratives, or automate workflows
• Large Language Models (LLM) fundamentals: purpose, capabilities, limitations (hallucination, bias, prompt sensitivity).
• Prompt engineering basics: how phrasing affects LLM output; techniques like role prompting, context priming, and chain-of-thought prompting.

Skills

• Communications Skills
• Facilitation Skills
• Numerical Reasoning skills
• Presentation Skills
• Problem solving skills
• Commercial Thinking Skills