Data Analyst II at Capitec Bank

• At Capitec, we believe better decisions start with better insights. This role exists to unlock the value of our data by turning complex information into clear, practical insights that help our teams make smarter decisions and deliver better outcomes for clients.In this role, you’ll work closely with stakeholders across the business to understand their needs, identify opportunities, and use data to solve real problems. Your insights will support how we design products, improve processes and measure performance — helping us grow as a truly insights‑driven organisation.If you enjoy working with data that has real‑world impact — and explaining insights in a way people can easily understand — this role could be for you.

What you'll be doing:
In this role, you’ll:

• Transform complex data into actionable insights that support business strategy and performance
• Lead and contribute to end‑to‑end data analysis initiatives with measurable business impact
• Analyse large, complex datasets using advanced analytical tools and techniques
• Partner with cross‑functional teams to understand business challenges and data requirements
• Build clear, intuitive dashboards and reports for decision‑makers
• Identify trends, risks and opportunities across products, processes and customer journeys
• Communicate findings and recommendations clearly to non‑technical stakeholders
• Apply your understanding of financial products, business processes and industry context to your analysis

What we're looking for
Minimum Experience : 

• An Honours degree in Analytics, STEM or a related field, with at least 5 years’ relevant experience, or
• A Bachelor’s degree in Analytics, STEM or a related field, with at least 8 years’ relevant experience
• Solid experience in data analysis, ideally within banking or financial services
• A proven track record of delivering insights that drive business decisions and outcomes
• Strong capability in advanced data analysis tools such as SQL, Python, R, Tableau or Power BI
• Experience performing complex analysis and statistical modelling
• Confidence working with cross‑functional teams to translate business needs into data solutions
• The ability to explain insights clearly and influence decision‑making at different levels
• A good understanding of financial products, industry trends and regulatory requirements, and how these affect data analysis

Knowledge

• Advanced proficiency in writing complex SQL queries, optimizing query performance, and working with large datasets.
• Expertise in advanced Excel functions, including macros and VBA.
• Proficiency in creating advanced visualizations and dashboards using tools like Tableau, Power BI, or similar
• Advanced skills in Python or R, including data manipulation libraries (e.g., pandas, numpy) and data visualization libraries (e.g., matplotlib, seaborn).
• Strong understanding of statistical methods and their application in financial data analysis.
• Understanding of predictive analytics techniques and their application in financial analysis.
• Knowledge of data modelling techniques to structure and organize data effectively.
• Understanding of risk analysis methods and their application in financial services.

Qualifications (Minimum)

• Bachelor's Degree in Analytical/Data/Technical or Other

Qualifications (Ideal or Preferred)

• Honours Degree in Analytical/Data/Technical or Other

Knowledge

• Advanced proficiency in writing complex SQL queries, optimizing query performance, and working with large datasets.
• Expertise in advanced Excel functions, including macros and VBA.
• Proficiency in creating advanced visualizations and dashboards using tools like Tableau, Power BI, or similar.
• Advanced skills in Python or R, including data manipulation libraries (e.g., pandas, numpy) and data visualization libraries (e.g., matplotlib, seaborn).
• Strong understanding of statistical methods and their application in financial data analysis.
• Understanding of predictive analytics techniques and their application in financial analysis.
• Knowledge of data modelling techniques to structure and organize data effectively.
• Understanding of risk analysis methods and their application in financial services.