Data Scientist Bootcamp

Ensure data solutions are built for performance and design analytics applications for multiple platforms. In addition to creating new database systems, data architects often find ways to improve the performance and functionality of existing systems, as well as working to provide access to database administrators and analysts.

Machine learning engineers create data funnels and deliver software solutions. They typically need strong statistics and programming skills, as well as a knowledge of software engineering. In addition to designing and building machine learning systems, they are also responsible for running tests and experiments to monitor the performance and functionality of such systems.

An Applications Architect tracks the behaviour of applications used within a business and how they interact with each other and with users. They focus on designing the architecture of applications as well, including building components like user interface and infrastructure.

BI developers design and develop strategies to assist business users in quickly finding the information they need to make better business decisions. Extremely data-savvy, they use BI tools or develop custom BI analytic applications to facilitate the end-users’ understanding of their systems.

Perform batch processing or real-time processing on gathered and stored data. Data engineers are also responsible for building and maintaining data pipelines which create a robust and interconnected data ecosystem within an organisation, making information accessible for data scientists.

A business analyst examines and analyses business processes. This professional finds efficiencies and takes on a leadership position when it comes to project teams. The business analyst provides necessary technical information for the business.