Top 5 Highest-Paying Data Analysis Jobs in South Africa

The world of cybersecurity and cloud computing is on the rise, and the demand for professionals who can design predictive models, derive insight from the data and manage data clusters for business intelligence and various other elements is higher than ever. Data mining, data visualization, data engineering, implementation of the data within the business intelligence related platforms, and other such derivatives are also on the rise. Data analysis remains the only true middle ground between all these interrelated disciplines and domains.

South Africa has become the central hub for the digital actions and innovations that are taking place today. It has become one of the central elements when it comes to the tech industry, cloud computing, and other such elements. Businesses readily adapt to the latest technology system that is made available to them, and that is why the need for the right professionals that can take care of an intricate process is increasing day by day. This is where the following data analysis jobs come into play.

Top 5 Highest-Paying Data Analysis Jobs in South Africa

Data Analyst

The data analyst is an entry-level job within the data science field, and the salaries can vary based on experience, certifications and other factors. These professionals visualize, parse, clean and look at the company's data. It’s a stable job, competitive and in demand, so completing a data analytics certification can help you gain an advantage over the competition.

You will work with plenty of teams and sections of the business, taking data from various nodes. After careful analysis, you’ll answer questions that decide the future of the business.

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Data Scientists

Data scientists do similar work as data analysts but with a twist. Data scientists have the liberty to pursue their own specific threads and ideas within the interpretation of data that is provided to them. These individuals also develop programs and software based on machine learning to predict the future trends by careful data speculation.

Data scientists can overlap with a variety of different things, such as machine learning, developing predictive analytical based models, and rendering help from AI. At times you will even have to design the whole architecture yourself, consult with various teams entitled to different departments to work with you, and spark a sense of collaboration on a whole other level.

Data Architect

This is one of the highest paying data science jobs worldwide, and the scope is pretty wide for this job, too. The main job of the professional is to create new system databases and use performance and design-based analytics to improve the interconnected data ecosystem within the company. The end goal here is to always make the information readily available by data scientists. It is an in-demand data analysis job in South Africa.

The main tasks of such professionals involve the building and maintenance of the company’s databases and identifying any structural or installation solutions that can be made available. Database administrators and database analysts are also to work with such professionals to ensure easier access to the company’s data and other possible reasons that involve working with the core processes and optimizing their performance.

Data and Analytics Manager

The data and analytics manager work in big data, and to do that such professionals have to coordinate with various managers of varied departments and align and strategize the business goals. These professionals also must have exceptional business and interpersonal skills. They also must-have dedicated experience with programming languages, such as SQL and NoSQL. The knowledge of machine learning, data analytics, and data visualization related tools is extremely awarding.

Machine Learning Engineer

There is a great scarcity of machine learning related projects, and it also might not be made part of such tools that consistently rely on a consistent influx of data. Machine learning can help the system derive valuable insight from the data and actually learn what is being taught or conveyed through the data. In this way, navigation, data interpretation and various other systems can reach their absolute potential.

The task of a machine learning engineer is to develop machine learning and deep learning systems. However, they also implement these into tools, software, and mobile-based applications. Further maintenance and optimization of the algorithms must also be done by the machine learning engineer.