Machine Learning Scientist

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This professional works with research and development of algorithms that are used to create intelligent systems. They build systems for product recommendations or to predict demand for certain products or services and explore Big Data to extract patterns from the data. If you enjoy research and have a strong background in Mathematics and Statistics, consider this career option.

5. Machine Learning Engineer

The work of a Machine Learning Engineer is similar to that of the previous career, but their focus is on creating a software solution that allows solving a business problem through predictive models. While the Machine Learning Scientist's objective is to chile email list research and develop new algorithms, the Machine Learning Engineer's objective is to apply these algorithms and create solutions. Applying Machine Learning algorithms requires knowledge of Mathematics, Statistics, data cleaning and pre-processing procedures, and at least one language related to Data Science, such as R or Python.

6. Business Analytics Specialist (Business Analyst)

In today’s complex business environment, an organization’s adaptability, agility, and ability to manage constant change through innovation can be the key to success. Traditional methods are outdated when it comes to achieving goals when economic conditions are unfavorable. That’s where business analysis comes in. Corporations achieve goals through projects that translate customer needs into new products, services, and revenue generation. Business analysts can make all of this happen more efficiently and effectively. The primary goal of a business analyst is to help companies implement technology solutions in a cost-effective manner, and to determine the requirements of a project or program and communicate them clearly to stakeholders, facilitators, and partners.

7. Data Visualization Developer

Data Storytelling is becoming crucial in any Big Data project. The ability to convert what Petabytes of data are telling you into a single graph or dashboard is almost an art, and there are many techniques and tools available for this purpose. Although there are tools that automate this process (or at least promise to automate it), this professional still needs to know more than just technology, but also when to use the right graph, how to use tables and reports, and especially how to use storytelling to present the conclusions of a data analysis project to a non-technical audience.

8. Analytics Manager

The Analytics Manager is responsible for the data analysis team. He or she coordinates the design, configuration and implementation of data analysis solutions, from infrastructure to defining data analysis tools and processes. Managing Big Data projects is not an easy task and the manager needs to have leadership skills and technical knowledge to understand the challenges inherent to Big Data.

9. Statistician

Although the profession of statistician is not new, it is being reinvented by the large volume of data and the new tools and solutions linked to Big Data. The role of this professional is to apply statistical techniques to understand data and help companies identify trends, make predictions and make data-driven decisions. Statisticians apply statistical theories and methods to collect, analyze and interpret data. They work for companies involved in market and public opinion research, for industries that need to perform quality control and develop new products, and – frequently – for municipal, state and federal governments.

10. Data Scientist

Data scientists are the data miners. They receive a huge mass of unorganized data (structured, semi-structured or unstructured) and use their skills in mathematics, statistics and programming to clean, process, transform and organize this data. They then apply their analytical skills – business knowledge, contextual understanding, skepticism of existing assumptions and machine learning algorithms – to discover solutions to business problems and contribute to decision-making and business strategies. This relatively new profession is the most in-demand profession in the US for the fourth year in a row, with annual salaries exceeding $100,000. Data scientists are professionals who know a lot about many things and their expertise is essential for building intelligent applications and analyzing Big Data.