Data science is growing every year, especially as businesses collect more data that needs to be analyzed. Because of its strong growth prospects, data science has become one of the most in-demand careers today. This means that it could be a great career for those who choose to pursue it. Data science is also a great career choice because it is needed in many industries and businesses are hiring experts to help them use this data to predict market trends, understand their customers better, to help with business development, and more. There are so many career paths within the data science world, and this article will focus on nine of the most lucrative ones.
Highly trained data science professionals usually end up becoming data scientists. Many of them help the businesses and organizations they work for by taking vast volumes of data and refining it into insights that can be used to make decisions or take the necessary actions. Because of how important their work is, data scientists have become an important addition to businesses and organizations of all sizes.
When completing a data science degree, you should put a lot of emphasis on gaining knowledge in statistics, math, modeling, and computer programming as these are the main skills most employers are looking for. Some organizations will require that you have some business knowledge and sense, especially if you will be hired to extract insights that will be used in the business decisions-making process. Additional skills you might need depending on the organization include being fluent in programming languages such as R, Python and SQL.
Once you start working as a data scientist, your primary role will extend beyond extracting insights from the data you are presented with. You will also be required to do so in a manner that helps other people understand this data. Remember that, as a data scientist, you will have a lot more work and responsibilities than a data analyst. For example, you will be responsible for creating the data models that data analysts can use.
Data scientists can be employed across numerous industries, but you will find many of them working for the government for larger businesses that collect the vast majority of data. Because there is a huge demand for data scientists across numerous industries, graduating with a data science degree means that your job search should be less stressful than if you graduated with most other degrees.
Although data analysts sit slightly below data scientists, their work is crucial because they analyze and also interpret data as well. The analysis and interpretation skills you possess become invaluable to businesses that rely on data to make decisions. Businesses will also hire you to find opportunities in various areas such as reducing customer acquisition costs, increasing revenue, and finding new growth opportunities.
As a data analyst, you will be required to use your skills to collect the right amount and types of data, analyze this data and transform it into usable information for the business or organization you work for to take advantage of. Data analysts can also be tasked with interpreting trends and patterns in the data they receive.
To become a data analyst, you need to complete a bachelor’s degree in an area such as data science or big data management. If you will be working in big data analytics, some employers require that you have a master’s degree. If you already have a data science degree, you can complete an online master’s in data science program which arms you with all the skills you need to follow the big data analytics specialization.
Data architects work specifically with data architecture. They design, implement, and manage the data architectures of the businesses or organizations they work for. Because of how involved and important their work is, data architects are often considered senior data scientists. It is quite difficult to get an entry-level job as a data architect.
Almost everyone working as a data scientist holds a master’s degree and has a lot of experience in the data science field. This could be a master’s degree in computer science or data science as these two overlap quite a bit at the master’s level.
To become a data architect, you will need about five years of experience working in data science, database administration, or programming. Here, you will expand your skills in data management, database design, data warehousing, data modeling, and more.
After that, you need to enroll in a master’s program to take your skills to the next level. Consider enrolling at Worcester Polytechnic Institute to complete their data science master online program which teaches you the technologies and tools you need to create, manage and implement complex and large-scale databases as well as to analyze the data within them.
Once you have completed your master’s degree, your likely employers will be technology manufacturers and software companies that can take advantage of your skills. However, data architects also work in finance, business education, and insurance, all of which require complex databases and data architecture.
If you have some business skills or want to work on the business side of things, then a career in data management is right for you. Data managers use their skills to help businesses achieve important business goals. They are also responsible for the flow of data within a business or organization, various data processes, as well as the coordination of people wherever the business needs it.
To be effective at their jobs, they must be knowledgeable in various areas including:
- Data quality collection and management
- Data governance
- Business intelligence and data warehousing
- Architecture and data modeling
- Interoperability and integration
- Overall management of master data, metadata, content, and other types of data
Depending on the business structure, a data manager can be responsible for the data domain of a single department, numerous departments, or the whole business or organization.
With everything they do, the role of a data manager can be summarized as ensuring the integrity of data throughout an organization or business, while ensuring this data is accessible in a secure way to every authorized person who needs it.
This is another role that data science graduates with some business savvy can thrive in. Business analysts examine and analyze business processes to unearth inefficiencies. Business analysts can also be called upon to lead various teams as well as provide technical support and information to businesses.
Many business analysts with data science skills work in the IT sector. However, they can work in any business department or type of organization their analytic skills are required. Depending on the organizations they work for, business analysts can be tasked with presenting data to a business, reporting to management, using data analysis to come up with various types of forecasts, identifying opportunities, and identifying any problems in business processes and procedures.
To become a business analyst, you require a degree with an emphasis on analytics such as data science, information systems finance, or related fields. A master’s degree can make you even more competitive in this field.
This is another very popular career option for data science degree holders apart from data science and analytics. Data engineers work a level below data scientists. This means they work with raw data before handing it over to other data scientists or stakeholders. Data engineers make data ready for data engineers to make use of by processing it. Because they work with several data forms and formats, data engineers should be proficient in several programming languages. These can include Apache Spark, SQL, Hadoop, and SQL. Python, Java, R, and C++ should also be part of their tools’ arsenal.
The work of a data engineer is very challenging because they are often working with unformatted data, with the only indication of the type of data they are looking at being the machine codes and other codes for where the data came from. This data will typically have human, instrument, and machine errors. It might not be properly validated and could have problematic records. It’s the work of data engineers to sort this data out to process it in such a way that a data scientist can know how to make use of it.
Data engineers also create data architecture and tools and then test them to ensure if they use them to store, access, and sort data, the data that was processed will be correct and usable. In addition to creating data architectures and tools, they are also responsible for their maintenance. Other than that, their job is analyzing, sorting out, and interpreting vast amounts of data.
Data engineers must have an intimate understanding of the various tools used in data analytics. Their knowledge of programming languages as well as what tools to use and when to use them is also incredibly important.
Lastly, data engineers can also be tasked with building the APIs that help support data pipelines in a business. If they build these APIs, then they work with front- and back-end developers, analysts, and product managers to help make use of the vast amounts of data collected.
A statistician is very different from a data analyst in that they focus on statistics instead of active data analysis. They are very good at identifying partners in various types and sets of data. Statisticians use statistical theories and techniques to collect, analyze and interpret numerical data. They are also tasked with applying hit statistical models, tools, and methodologies to solve real-world problems. They also communicate their analysis findings to various stakeholders so they can take action depending on this data.
Because they are the ones who find connections between various types of data, they are essential in business decision-making and policy creation policies. Statisticians also work in numerous fields, but you will find many of them working in medicine, science, education, government, and business.
Machine Learning Engineers
Machine learning engineers build working software, and to ensure the software works as expected, they have to possess both software engineering and data science skills. Their work is very different from other data scientists who collect, analyze, and visualize data.
A machine learning engineer is tasked with creating artificial intelligence machines and systems. These machines can then be used to learn and apply the knowledge they learn to make data analysis easier.
To do all this, data science graduates must have deep knowledge of data sets and how sophisticated algorithms work. Other skills they must have include data modeling and evaluation, probability and statistics software engineering programming, and computer science and machine learning algorithms.
Machine learning engineers start with a bachelor’s in computer science data science, gain a few years of experience, and then complete a data science or computer science master’s degree that arms them with the machine learning skills they need to enter these roles.
Data is becoming very valuable for business, especially in marketing, and this is why the demand for marketing analysts who possess a business and data science degree is soaring. These professionals must possess both statistical and software skills. However, their roles push them to focus more on the business side of things instead of the analytics one.
Marketing analysts analyze marketing data to provide a business with marketing insights regarding their goods and services. They are, therefore, important in helping businesses see every aspect of their marketing including how each campaign is performing, where and how a business can reduce customer acquisitions cost, which marketing channels are working best, and which strategies are producing the best return on investment.
Marketing analysts can also be tasked with using the data they have and the insights they get from it to develop new marketing plans, implement strategies, and advise their clients on how best to improve their marketing campaigns. They also develop models for testing various aspects of their clients’ marketing to find areas of improvement.
Earning a data science degree opens up numerous career options depending on where you want to work and how you want to work. If you are about raw data, career options that focus on data such as data engineering and data analytics will be best for you, but if you love the business side, options like business analysis and statistician would be great.