The field of data science has been growing explosively in recent years and shows no signs of slowing down anytime soon. Why? Because big data is already playing a vital role in a variety of fields and will only become more important in the future. Over 90% of the data currently in the world was generated in the last two years, and data science job openings are expected to be in the millions by 2021. This means a rich field of employment opportunities for data scientists and a chance for aspiring data scientists to get in on a rapidly growing and lucrative career path.
Top Trends in Data Science in 2021
Machine learning, predictive analytics, the Internet of Things (IoT) and cloud technology are just a few of the fastest growing trends in data science right now. The fields of health care, ecommerce, marketing, insurance, real estate and more have all come to embrace data science as a vital part of doing business. Knowing how to use the mountains of data now regularly collected by large companies will be an invaluable skill for the foreseeable future.
The 5 Top Data Science Jobs
So, what skills and qualifications will you need to land a top-flight data science job in 2021 and beyond? To find out, let’s have a look at the most lucrative and sought-after jobs in the field.
1. Data Scientist
Data professionals are in high demand in medical, financial, and science companies worldwide. A data scientist must be able to use a wide variety of techniques such as computer modeling, statistics, analytics, and math to glean insights from raw data and help organizations make major decisions based on those insights. While it can be a challenging field of study, the rewards are worth it — those getting their degree in data science can expect to command a salary of $100,000 a year or more.
2. Data Engineer
A data engineer’s primary role is to take raw data, find trends and insights in the data sets, and develop algorithms for making that data more comprehensible (and thus useful) for the client or company. This involves being skilled in a number of programming languages, as well as commanding knowledge of SQL database design.
But to build a useful algorithm, a good data engineer must also have strong communications skills, so they can understand their client’s objectives and help work to meet those goals.
A data engineer must also be able to identify data reliability, conduct research, master statistical methods, and automate tasks. Some of the top tech companies, such as Amazon and Hewlett-Packard, pay their engineers an average of $134,000 a year or more.
3. Data Analysts
While there is some broad overlap between the different fields of data science, there are subtle differences in specialities. A data analyst’s primary role is to help shape raw data so clients and stakeholders can use it to make important business decisions. While data analysts must still have a strong command of SQL databases (like data engineers), data analysts will also work extensively with spreadsheet software and visualization tools like Tableau or Qlik.
In essence, the data analyst acts as an all-important bridge between raw data and those who must make business decisions based on that data. The average data analyst can earn anywhere from $60,000 to $140,000 a year.
4. Machine Learning Engineer
Where a data analyst’s job is to glean insights from data and produce results or answers useful to a human audience, the job of a machine learning analyst is to design software that will automate those insights without human intervention. The software developed by a machine learning engineer uses the data it gathers to carry out future operations with more accuracy.
A common example of this sort of machine learning would be the algorithms used by streaming services and video sites like YouTube — the algorithm analyzes a user viewing behavior, recommends content based on that analysis, and refines those recommendations based on ongoing input. With more data being generated daily than could ever be manually analyzed, machine learning is rapidly becoming an invaluable part of doing business. Machine learning analysts can expect a salary of $100,000 to $130,000, depending on their skill set.
5. Business Analyst
The job of a business analyst is to help improve an organization’s decision-making process by interpreting and analyzing data. A business analyst uses the data they gather to identify best practices and goals and communicate those goals effectively to the management team. A good business analyst must not only have the skills to research and evaluate the processes and goals of their business but also make sound and understandable recommendations based on that analysis. This may require more robust communications skills than other data scientist fields, but a business analyst working in the field of information security or operations research can expect a salary in the range of $80,000 to over $100,000 a year.
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