Machine Learning Engineers are required to build machine learning systems as well as implement and maintain machine learning market applications in technology and business products. Using Keras library in TensorFlow, the key focus of the system is scale-ability. This career path requires expert-level programming skills in ‘R’ or Python and comprehensive knowledge in machine learning models and their applications according to the business sector needs.

Data Engineers design, build and maintain data structures for large-scale technology applications, as well as supervise and manage an entire data life cycle. This career path requires strong software engineering and learning skills.

Data Scientists perform advanced technical analysis to understand complex systems and make related forecasts about them. This is done by using scientific and mathematical methods such as statistics, mathematics and computer science with the main mission of extracting useful patterns and insights from data. The results are demonstrated using statistical models, visualizations and product data.

Data Analysts are expected to use and implement tools such as Excel, SQL, ‘R’ or Python and conclude data to answer specific questions. Data Analysts must have a deep understanding of the organizations’ data. This career path requires some visualization of data to guide the organization to make valuable judgments by taking and implementing key business decisions.