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Data Science is an emerging field that will become more and more important over the next decade as companies scramble to take advantage of the huge amount of data they have at their disposal and make sense of it in order to improve their products and services. Data Scientists are currently some of the most in-demand professionals, but just what kind of jobs will be available to Data Scientists by 2023? Here’s everything you need to know about what data science jobs will be available in 2023 and where you can learn more about them today so you can prepare yourself for the future job market!
These folks develop complex software and algorithms. According to CyberCoders’ recent study, demand for software developers with Python skills will increase by 600% over the next four years. However, R jobs are expected to grow even faster—by 1,400%. So, if you are a Python developer and interested in working in the data science industry, consider learning R. By switching your coding language you can enhance your opportunities not only on the job market but also enable yourself more paid freelance gigs as companies will find it easier to hire programmers able to write code using multiple programming languages rather than writing their code using one specific language.
A role that uses programming, statistics, and machine learning to analyze data and generate new insights. Using visualization tools, data analysts help communicate their findings to a variety of audiences in different sectors. For example, finding ways to improve customer experience on e-commerce sites or developing algorithms for traffic predictions could fall into a data analyst’s purview. Though you might have to pass through more technical roles like programmer or database developer first, it’s an entry-level position with great growth potential—you can advance from there to become a senior analyst (i.e., manager). Most importantly, today’s businesses are looking for people who know how businesses operate and can apply what they know about business intelligence (BI) and analytics.
Machine Learning Engineer
Do you want to be on the bleeding edge of data science and machine learning, analyzing reams of data to discover hidden insights and make predictions about future trends in healthcare, business, or society at large? Machine learning engineers specialize in using algorithms to find patterns in data sets. This career is all about learning from your mistakes. Machine learning is a field that’s always evolving, which means it takes experience to find what techniques work best for certain problems. If you know Python and R or have experience with Apache Spark, Apache Hadoop, or Java SE (7), then you’re set—these are all programming languages commonly used by machine learning engineers. If not, there are plenty of tutorials online that will help get you up to speed.
Business Intelligence Manager
As they say, nothing beats experience. And a lot of business intelligence (BI) managers have experienced data science in their previous roles—especially because of a dearth of BI talent across industries. Business intelligence is similar to data science in many ways and will also require new skills to create insightful reports and dashboards that can analyze large amounts of data and make recommendations based on it. If you want to get into BI but aren’t sure where to start, check out our free guide: 8 Steps To Become A Business Intelligence Analyst And Start Your Career With Analytics. You’ll learn what kinds of skills are needed for these roles, why you should consider becoming one, and much more.
Are you aspiring for a booming career in IT? If YES, then dive in
Big Data Architect
The data architect is focused on helping define, design, and oversee how enterprise data flows through an organization. The role usually exists within larger organizations that have a dedicated IT department and integrates with other business departments. A big-data architect works to integrate disparate systems so they can all be leveraged by data scientists in some capacity. Architects work closely with database administrators (DBAs) to make sure that projects are met on time, on budget, and within scope. These roles don’t normally require extensive technical skills, though more specialized DBAs may need training in a database management system like MongoDB or Cassandra. Database engineers will also likely be trained in programming languages like Java, C++, Scala, Perl, or Python. To land an entry-level position as a Big Data Architect requires at least two years of relevant experience in IT administration and knowledge of computer science fundamentals at the bachelor’s level or higher.
Big Data Administrator
A growing number of companies need someone to keep their data safe, secure, and accessible. That’s why jobs for big data administrators are expected to increase by 27% over 10 years (that’s much faster than average). Big data admins have to make sure their company has enough server space and computing power to store all that valuable—but also vulnerable—data. They also help define policies about which employees can access what information. The growth in big data jobs is likely due to increased concerns about privacy: with more sensors being built into devices, large amounts of sensitive information are becoming available digitally every day. With those insights come risks, so businesses will be looking to protect themselves from those security threats. And it helps that it isn’t hard to hire a talented data scientist or analyst: they’re among some of our most popular profiles on LinkedIn! You’ll find many opportunities listed under Big Data Scientist or Big Data Analyst. Just remember—as a professional who works with people’s personal data, you’ll need a background check before you land your first job; most states require one. It takes three months on average.
Big Data Developer
The need for data scientists continues to grow as firms increasingly demand actionable information from their data. As a Big Data Developer, you will be tasked with creating automated solutions to mine massive amounts of information and derive specific insights from that data. While previous experience in coding languages such as Python or R is helpful, it is not a requirement for all positions. Training programs do exist, but many employers are looking for candidates who have demonstrated prior interest in analytics and computer science through online courses and projects. Candidates should also have strong problem-solving skills and be able to communicate effectively with team members. Pay for Big Data Developers averages $104K per year. If you are interested to learn new coding skills, the Entri app will help you to acquire them very easily. Entri app is following a structural study plan so that the students can learn very easily. If you don’t have a coding background, it won’t be any problem. You can download Entri app from the google play store and enroll in your favorite course.
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