Data Science Focus Areas
However, data science is a massive field – so massive that it is impossible for any individual to gain expertise on every aspect of it. Instead, there are numerous specializations available to those who pursue careers in data science. These track with the different focused job responsibilities of data scientists at large companies.
So how do you figure out which area of data science is the one for you? It comes down to your existing skills and areas of interest, as well as which industries you are most drawn to working in. The guide below gives an overview of the different data science focus areas to help you determine where you would like to plot your thriving career.
Data Science Job Growth and Salary Range
Indeed, data science is one of the most rapidly growing industries there is at this moment, with the Bureau of Labor Statistics reporting an estimated job growth rate of a stunning 36% by 2031, with no signs of slowing down after that. This should come as a tremendous source of encouragement for those considering entering the field, as it all but guarantees that good work opportunities will always be available for qualified candidates in the data sciences.
Prospective data scientists should also feel heartened by the projected salaries in the field: the Bureau of Labor Statistics reports a median annual income of $100,910 per year across the entire data science industry. In short, if you are working as a data scientist, you are likely to be paid well.
Data Science Specialization Categories
Typically, a data team at a large business will feature people with a variety of skill sets who each play their own specific roles. Though they often work closely with one another, these can be vastly different positions within a company, calling for their own specific approaches and strengths.
You will need to choose your data science focus areas at the outset of your career, as each sub-discipline of the data sciences requires extensive training. This doesn’t mean that it isn’t possible to expand your horizons later in your career, but this is not a field in which it pays off to be a generalist.
Read on to learn more about different data science specializations to find the area where you will thrive.
Data Engineering and Data Warehousing
Data engineers tend to deal with data in its rawest forms, processing it through a variety of systems so that it can be used by other members of the data team for analysis. They are also responsible for managing a business’ data warehouse, one of the primary places that a company’s information is stored. In short, this is a crucial job on any team, as it means you are responsible for one of the company’s most foundational components.
Education needed: To get a Master’s in Data Science with a specialization in Data Engineering, one typically is expected to hold a bachelor’s degree in a related field, such as computer science or statistics.
Data engineer median annual salary:
Some of the top data engineering positions have the following job titles:
- Data analyst
- Data engineer
- Data scientist
- Database developer
- Computer systems analyst
- Computer network analyst
Database Management and Architecture
Just as architects design buildings, data architects design the digital framework within which a company works. This is a high-ranking information management position that can often work closely with the leader of an organization to ensure that its data architecture is supporting the business’ mission as efficiently as possible. Many who become data architects start their careers as data engineers and work their way up as they gain a more advanced understanding of how database systems can be optimized for businesses.
Education needed: To get a master’s with a specialization in database architecture, one is typically expected to hold a bachelor’s degree in data science.
Job titles for data architects include:
- Database administrator
- Data administrator
- Database architect
- Information modeling engineer
Data Mining and Statistical Analysis
Data mining is a form of statistical analysis that aims to interpret the information a company collects. This uses descriptive and predictive analytics, which employ algorithms to find trends and audience insights that can help a business maximize its offerings. This job involves both extensive work in statistics and the difficult work of communicating complex findings to those who don’t understand the language of big data.
Though statistical analysis is its own data science specialization, in fact, there are also many subspecialties of statistical analysis. For example, some statistical analysts work specifically in the field of marketing, using sophisticated data tools to help companies plan the most effective campaigns possible. This is just one example of one of the subfields of statistical analysis.
Education needed: To pursue a master’s with a concentration in data mining, students typically have a bachelor’s degree in a related field, with coursework in calculus, programming, and of course, statistics.
Some of the top job titles for statistical analysts include the following:
- Statistician
- Data analyst
- Data mining analyst
- Marketing analyst
- Quantitative analyst
Cloud and Distributed Computing
Cloud architecture and computing specialists specifically aid organizations in their cloud storage management systems. Cloud storage has become a standard – even mandatory – part of how business is run today, and small issues with cloud systems can easily create huge trouble for businesses. This means that cloud engineers will always be in demand, as their expertise can address crucial issues to keep a business running properly.
Education needed: Those who hold a master’s degree with a concentration in cloud and distributed computing most often have bachelor’s degrees in information technology or computer science.
Top jobs for those who specialize in cloud architecture include:
- Cloud engineer
- Platform engineer
- Cloud architect
Business Intelligence and Strategy
Those who specialize in business intelligence and strategy oversee the systems by which data is translated for key company decision-makers to directly inform business strategy and market knowledge. This is a highly impactful role that requires great expertise, as you will be entrusted with conveying information clearly and accurately, with a nuanced understanding of what your company’s leadership seeks to achieve with their business. For those who excel in the fields of statistics and business, this is a perfect option to marry these two skill sets in a rewarding and stimulating profession.
Education needed: Those who pursue a Master’s in Business Intelligence typically hold bachelor’s degrees in the fields of mathematics, computer science, and statistics.
Some of the top job titles for those specializing in business intelligence include the following:
- BI developer
- BI engineer
- Data strategist
- Marketing analyst
Machine Learning (ML) / Cognitive Computing Development
Perhaps one of the most famous branches of data science due to its frequent appearances in science fiction, machine learning is concerned with making robots to improve a company’s efficiency and be sure that they are using the most up to date algorithms and models to advance the possibilities of automation within their business.
Education needed: Those who pursue a master’s with a specialization in machine learning tend to hold bachelor’s degrees in applied mathematics or statistics.
Job titles for those who work in roles related to machine learning include the following:
- ML Engineer
- Cognitive Developer
- AI Specialist
- ML Researcher
Data Visualization and Presentation
Data visualization specialists do the difficult work of conveying complex statistical information in ways that can be accessible to those who are not versed in data science, including executives of companies who will be relying on your information to make key business decisions. This is an engaging and rigorously intellectual job, requiring you to think about numbers and data at the same time that you think through other ways of communicating about the same concepts.
Education needed: To get a master’s degree with a concentration in data visualization, students typically need to hold a bachelor’s in computer science, engineering, or graphic design.
Some of the job titles for those who focus on data visualization are the following:
- Data visualization engineer
- Data visualization architect
- Software developer
Operations-Related Data Analytics
Operations-related data helps a company understand its own competencies and deficiencies so that they can get a complete and accurate picture of their inner workings. Operations data analysts are entrusted with conveying this information clearly and effectively to company leadership and helping find areas for improvement. This can be a less technically-oriented job than some other data science career paths, so if you are more interested in problem solving than the language of big data, this could be one of the best data science focus areas for you.
Education needed: Master’s students in operations-related data analysts most frequently hold bachelor’s degrees in applied mathematics.
Top job titles for those who specialize in operations-related data analysis include:
- Communication analyst
- Planning analyst
- Decisions analyst
Market-Related Data Analytics
Those who specialize in market-related analytics help businesses understand data related to customers and sales to help inform a company’s overall direction for marketing. Similarly to operations data analysts, these specialists can contribute to key strategic decisions and are entrusted with providing accurate and easy-to-digest information about pertinent information. This is a wide-ranging data science specialization that can take different forms at a variety of different businesses.
Education needed: Those who receive master’s degrees with specializations in market-related data analytics most frequently hold bachelor’s degrees in statistics.
Top job titles for those who specialize in market-related analytics include:
- Market analysts
- Product analysts
- Web analysts
- Sales analysts
Sector-Specific Data Analytics
Many industries require an intensive understanding of highly elaborate systems that are not analogous to other business models. These can include the healthcare industry, insurance, finance, and more. There are data science focus areas that can help people build expertise in these fields to build long-lasting careers doing analytics work for the industry in question.
Education needed: To receive a master’s with a data science specialization in sector-specific data analytics, one typically is expected to hold a bachelor’s degree in statistics.
Some of the top job titles in sector-specific data analysis include the following:
- Data scientist
- Data analyst
- Business analyst
Taking the Next Steps to Start a Career in Data Science
If you are excited by one or more of the data science focus areas listed above, it is time for you to take the next steps toward pursuing a master’s degree that will open doors for you. The time has never been better to become a data science professional.
To learn more about program offerings for each data science specialization, visit our guide here.
To learn more about the path and lifestyle of a data scientist, take a look at our career guide here. To learn more about other programs related to data science, check out our list here. For an index of everything you need to know to pursue a Master’s in Data Science, visit our homepage.
