According to Glassdoor, data science has been the number one job in the US market. One of the key reasons why data science continues to be such a great career is due to the numerous career options it offers. Data science is not one specific job title, but a discipline that provides lots of professional options, and we are going to look at some of the best below.
Data Science Generalist
Many data scientists start their careers as generalists or analysts where their jobs entail discovering useful insight from the mountains of data they handle. They use exploratory and experimental methods and techniques to discover hidden insights inside data, simplify complex data and provide insights that form the basis of informed predictions.
Data science generalists often work as analysts for the government, non-governmental organizations, and various industries. In addition to their math and computer science skills, data scientists must also possess incredible problem-solving skills and the ability to dissect data in ways most other people cannot.
They also possess the skills to understand work done by data scientists in more specialized areas of data science.
Machine Learning Engineers
Machine learning engineers now form a large part of the data science community. They understand various machine learning models, intuitively understand how they work, and then use them to provide solutions to problems.
Machine learning engineers often work as developers or analysts. Analysts use the various machine learning models that are available to find relationships within complex pieces of data. Developers, on the other hand, create models that use the power of machine learning to solve various problems. For example, they may use machine learning and artificial intelligence to develop chatbots for the hospitality industry.
Both the developer and analytics machine learning engineer paths require different amounts of work and skills. While analysts do not have to think about creating final products or software, developers have to create products that perform according to requirements and specifications. Because of these two lucrative career paths, a career in machine engineering remains one of the top options for those who complete the online data science masters program at Kettering University. It is one of the most lucrative data science careers considering how prevalent the use of machine learning is in the modern world.
Machine Learning Scientists
Machine learning scientists research and develop new approaches to data and algorithms. These approaches are included in adaptive systems such as deep learning techniques, supervised and unsupervised systems.
A lot of their work is then used by machine learning engineers or data scientists working on artificial intelligence models and techniques. Machine learning scientists are also known as research engineers and research scientists.
Data Engineers
Modern businesses collect a lot of data. The data comes from various sources including social media, point of sale terminals, marketing efforts, online sales, supply chains, and many others. This data will often be collected in various formats. Data engineers create the infrastructure required to ensure the proper movement of this data from all these different sources to one storage or analytics platform.
These engineers are critical for all organizations that collect data either in high volumes or from numerous sources. Data scientists have the distinct advantage of working on whole data sets instead of being tasked with dealing with data subsets or subsamples. The two main types of infrastructure these engineers work on include data warehouses and data pipelines. These are used for data storage and transportation respectively.
To ensure data can be analyzed the right way, data engineers develop the systems that move data into various analytics platforms. This process transforms data into formats that can then be used by specific analytics platforms. All of this is done without any interference with or disruption to existing data storage warehouses.
Data engineers have superior programming skills compared to other data scientists, but their skills do not usually include in-depth statistical knowledge, although it is still necessary for some areas of their work.
Business Analyst
Business analysts do not often have the technical skills data scientists have, but they have a deep understanding of business processes and business intelligence. Business analysts are often the bridge between the business and data scientists and are often tasked with ensuring strategic business objectives are met.
Many business analysts often develop various deliverables like reports and presentations to ensure the data that comes into the business can be understood by everyone in the organization. Because of this, they will also have data analytics and visualization skills.
The duties of a business analyst and a data analyst will often overlap. This career option is great for those who understand complex data and who have an interest in business development and management.
Marketing Analyst
These are also data analysts, but their focus is on marketing aspects. They only deal with marketing data and break it down to help businesses make the best marketing decision. They can also analyze the market to help businesses see and take advantage of marketing opportunities.
Because they deal with large data sets, they must have solid math, analytical, statistical, and problem-solving skills. In many cases, those with a data science degree use market analytics roles to get into other data science roles.
Investigative and Data Journalism
There is a need to analyze data and present it in a way that the public will understand in popular media including social media, newspapers, and news websites. The use of data to perform investigations has been used for decades, with a prominent example being the Panama Papers leaks. Journalists were able to analyze over 11.5 million documents to come up with graphs and other types of information that people could understand.
Data journalists must see and understand the connections between different types of data. Data science enables these journalists to do their analyses at a larger scale than they could otherwise.
A degree in data science leads to lucrative careers anywhere data is involved. This can range from government organizations to the offices of prominent newspapers. The good news is that advanced degrees in data science can be completed online so you can advance your career while working.