Data Analyst at Capitec Bank

Purpose Statement

• The Data Analyst role exists to unlock value from data by making data accessible and meaningful to stakeholders across the organization. This role transforms data into actionable insights that support strategic decision-making, optimize operations, and drive business performance. By identifying trends, patterns, and opportunities, the role enables informed, data-driven decisions and contributes directly to the company’s strategic objective of being an insights-driven organization.

Experience

• NB. Length of experience required is conditional on the qualifications obtained but must include: 
• Experience in data analysis, with a significant portion in the financial services or banking sector
• Proven track record of leading data analysis projects and driving business impact through data insights
• In using advanced data analysis tools and software (e.g., SQL, Python, R, Tableau, Power BI).
• Experience in performing complex data analysis and statistical modelling.
• Experience working with, guiding and providing subject matter expertise to cross-functional teams (e.g., finance, marketing, IT) to understand business needs and provide data-driven insights.
• Of communicating and presenting findings and recommendations to non-technical stakeholders.
• Understanding of various financial products and services, industry trends, industry regulations and compliance requirements and their impact on financial data analysis

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.

Skills

• Analytical Skills
• Communications Skills
• Problem solving skills
• Project Management Skills (Methodolgy Specific)