If you are looking for a job in Data Science, we have startling news for you – the number of job openings in the field is growing remarkably as more and more employers seek to hire Data Scientists, Data Analysts and many more Data Science job profiles. 2023 is shaping up to be the year of excellent job opportunities if you any way relate your skills with big data analytics.
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The world today is getting ‘Big Data’ crazy, and data scientist is the hottest job yet again this year. But the dilemma is to choose what skills will get you identified by top employers. It is a major concern of major professionals and students that if they know Java, will it be helpful in driving the career to the Data Scientist level? What are those certain skills that increase your credibility even more and force employers to choose you over others?
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Recently, Data Science crowdsourcing specialist, CrowdFlower Inc. surveyed to identify what are the most-wanted Data Science skills that will give you the top-row ticket in your dream company. The experts analyzed more than 3500 job positions on the popular professional website, LinkedIn.com for data science jobs and created a report with the real-time data. It has listed top 21 individual skills that are most frequently expected from a data science professional. The results bring forward the best to guide you in acquiring brilliant jobs with high salaries and even prepare for your Professional Certification Course – CCP: DS.
No wonder, SQL sits in the top position for you to develop as a data scientist. SQL is the most looked for competence if you want to make a big difference and be productive from day1. More than 55% of the job postings relating to this discipline on LinkedIn require expertise in SQL. Hadoop raised its graph for the second position. As evident, data science is a lot about dealing with excessively growing data and no technology than Hadoop has until now made it to the first place.
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Whether it is a search engine like Google, social media giants like Facebook, LinkedIn, Twitter or software companies like IBM, Accenture, Adobe or the very promising e-Commerce Amazon.com, all are using Hadoop for accessing and analyzing huge volumes of data in minimum time. Therefore, Professional Big Data and Hadoop Training is a must-have to make a better career in this 21st century. On the contrary, it was strange to see that Apache Spark is not that prominent as Hadoop for a data analyst.
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In context to the rankings, CEO and founder of CrowdFlower said, “It’s not surprising the two skills that are at the top are SQL and Hadoop, which are the technologies that actually store the data,” He further mentions, “Every data scientist has to know how to get the data out. If you can’t get the data out in the first place, you can’t do anything.”
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However, the next name on this list is a little surprising to all the experts and professionals. Second highest in the list of PPYL Popularity of Programming Language Index, Python is the real winner in programming. For you to make your space in this big data realm, you ought to have in-depth understanding and hands-on preparation for Python and its toolkit. It is indeed the third critical finesse for the upcoming jobs in data science this year.
This may have come up due to the fact that Python toolkit is getting better and releasing more advanced ways of working in Python environment. It also indicates that Data Science is not just about analytics and statistics, it is a lot more into programming.
Next in the row are Java and R Programming. Java certainly is ubiquitous. No matter how much we prosper in technology, Java will continue to be a great programming language for most tools and platforms. It plays a prominent role in the life of Developers, Project Managers, Hadoopers, Mobile App Developers and many other IT and business aspirants. In reality, Java does not make much sense when it comes to Data Science in particular, but since Hadoop shows its prominence, we can’t ignore Java.
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R Programming is meaningful here with its powerful statistics and is to be embedded in your skill set. Having the most relevant analytics skills for a field like data science, R rightly occupies its place among the top five skills for data science.
So we are clear with SQL, Hadoop, Python, Java and R analytics programming language as the five top technology and platforms you should acquaint with before applying for any data science jobs in the upcoming days.
Climbing the ranks are Hive, MapReduce, NoSQL, Pig, SAS, C and Oracle that encompass big data-related jobs and command high salaries for a Data Scientist profile.
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The recent Harvard Business Review (HBR) explains, “A data scientist is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data. The title has been around for only a few years. (It was coined in 2008 by one of us, D.J. Patil, and Jeff Hammerbacher, then the respective leads of data and analytics efforts at LinkedIn and Facebook.) But thousands of data scientists are already working at both start-ups and well-established companies. Their sudden appearance on the business scene reflects the fact that companies are now wrestling with information that comes in varieties and volumes never encountered before.”
The main, important observations and conclusions you can make from this in-depth research by CloudFlower are:
- Familiarity with SQL and profound insights into SQL Developer and SQL Server data storage skills will make you more desirable candidate for the top job positions. Hadoop is equally important for you to make the best Data Managers in any company you aspire.
- Evident enough, anyone wanting to build careers in data science field must be competent as a Python Developer and significantly work on their programming skills in Java and R.
- For a Professionally strengthened career, get yourself equipped with both database and programming such that you can enrich your data rather than just analyzing it.
The opinions expressed in this article are the author’s own and do not reflect the view of the organization.