Capitec Bank is a South African commercial bank. As of February 2017 the bank was the third largest in South Africa with 120,000 customer opening new accounts per month.
To simplify banking, we’ve developed an all-inclusive banking solution. Global One is the one solution that enables you to transact, save and access credit in realtime. We also believe in ...
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, preferably within the financial services or retail sector.
Experience in contributing to data analysis projects
In using data analysis tools and software (e.g., SQL, Python, R, Tableau, Power BI).
Experience in performing data analysis and statistical modelling.
Experience working with cross-functional teams (e.g., finance, marketing, IT) to support business requirements and the provision of data-driven insights.
Ability to communicate findings and recommendations to non-technical stakeholders.
Exposure to financial products and services and market trends and their impact on 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
Basic understanding of basic SQL commands and queries to extract and manipulate data.
Proficiency in using Excel for data analysis, including functions, pivot tables, and basic formulas.
Familiarity with basic features of Data Visualization Tools Power BI, or similar.
Basic knowledge of programming languages (such as Python or R) for data analysis tasks.
Understanding of fundamental statistical concepts and their application in data analysis.
Understanding of data cleaning techniques to ensure data quality.
Knowledge of descriptive statistics to summarize and describe data.
20 Initiatives to Boost Employee EngagementAre you struggling with improving employee engagement at work? This article covers everything from better communication to building a strong workplace culture.
30 Common Interview Mistakes to AvoidThis piece examines 30 of the most common mistakes applicants make at interviews, so you know how to better avoid them.
Gmail
Yahoomail