Top 6 Trends you should know to become a Data Scientist

Nowadays, the demand for Data Scientist is increasing rapidly, and the aspirants who have the correct blend of skills in Data science will be satisfied with a profitable career in this field. Also, the candidate who wishes to pursue his or her career as a Data Scientist should be aware of the important data science trends. Data plays an essential role in every organization. It is the new business currency now. A wide-ranging impact has been observed in Data Science area, and thus, there is a high demand for a lot of new job opportunities and skill sets. Well, to become a Data Scientist is not an easy task, in order to achieve this a candidate should hold positive and flexible skills set. A Data scientist has to go through a massive amount of unstructured and complex data to find the results for effective business processes which help to accomplish specific business requirements. A Data scientist not only have to deal with data, but they should also possess knowledge in Data designing, programming, analyzing, visualizing and testing. Data Scientist is a lucrative career. It has been ranked as the number one job in the U.S. by Glassdoor. According to a report by the Bureau of Labor Statistics, the increasing demand for Data Science will open around 11.5 million jobs by 2026. In 2016, the average salary of a Data Scientist was more than $111,000. Data Scientist is a growing career, and it will remain highly competitive in the market. If you want to make a successful career in Data Science field, then you should know about six global trends.

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1. Maintain your technical abilities: If you want to pursue your career as a Data scientist, then you should not limit your knowledge within a single technology. Data Science primarily involves the programming languages, i.e. Python and R. Most of the Data scientist utilizes these programming languages. Data Scientist should learn these programming languages very well, as Python and R are now used as the most skillful tools to be used in any industry. According to the studies, R is broadly used language, but Python is gaining more popularity due to its flexibility, ease of use and reliability, and it is expected that it will remain at the top in the upcoming years. Data Scientist uses some more programming languages, MATLAB, Java, C/C++, and SQL are few of them. Well, apart from these, Apache Hadoop is evolving as the popular framework in Data Science field.  Most of the organizations are using NoSQL, HBase and MongoDB databases to store a huge amount of complex data. There are few additional tools such as Power BI, Teradata, ETL and IBM Db2 which are used in the data management sector. A Data Scientist should be aware of these tools.

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2. A candidate must have robust Business Intelligence Skills: Business intelligence is an evolving field; thus, a Data Scientist should learn it. Business intelligence skills need the ability to elucidate the data set which provides visual analytics to decision makers of any organizations that help them to take better business decisions. This will support them to improve the value of their work. A professional Data Scientist should have excellent communication skills and should be able to explain the data and describe the perceptions and analytics which they have collected form data mining and confirm the brief and the definite work. The other skill sets are SQL and Tableau which help to enhance your skills. These tools will help you to simplify your data management and data visualization capabilities.

3. Experience in Data Analytics is important: Data analytics skills are important which can be achieved with the help of machine learning. Data analyst plays a critical role in the Data science field because most of the industries want to manipulate and clean their data so that they can create reports which provide a clear outline of their business. To analyze a large data set, numerical investigation is one of the essential skills. This will support you to enhance your skills require to carry out experimental study, measure your data approach and implement machine learning. Data Science is a broad domain which often combines with the machine learning, Artificial Intelligence, and deep learning.

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4. Data Scientist is required in almost all industries, but the candidate should try to proficient one: The role of a data scientist is not limited only to one leading business. The manufacturing and retail, financial services, logistics sectors are all evolving in the market along with recent development in the popularity of government absorbed Data scientist roles. But the part of the Data scientist expected to be pervasive through all industries. It is said that companies are searching for industry-specific experience person; thus, you should explore in your chosen sector and refine your talent to make your resume more attractive for the recruiters. Data Scientists have a major concern about the financial services industry, security and compliance, and fraud detection.

5. Should be able to balance strong academic successes with on job training: Most of the Data Science roles need a doctorate in statistics or mathematics from a reputed university. Well, this is not a prerequisite for all data scientist role, a Ph.D. degree will grab the attention of the probable employers because most of them working as a Data Scientist will have a Ph.D. Apart from having a Ph.D. degree, a candidate will also require building certain skillsets to meet the specific industry requirements. This can be achieved by joining professional development courses, boot camps or online training classes. Moreover, you may want to actively participate in more approaches and get a big-data certification which will help you to enhance your resume. Well, updating your skills is essential in terms of growth, and thus the candidate should be aware of the latest trends and technologies. In order to learn new technologies, you should know your area of interest and which technology you want to proficient.  You can achieve this by attending classroom training or conferences and meetings. A candidate should be able to balance formal training with on job training. 

6. The growing demand for data governance: General Data Protection Regulation is in effect from 25th May 2018, and it is directly affecting Data Science. Most of the companies are still understanding the limitations of this new regulation. It includes the two essential topics data privacy and right to explanation. The GDPR will reinforce the data protection privileges for all people within the European Union. It is foreseen that regulation will create demand for around 75,000 data protection officer positions regularly. Within Data Science, the GDPR executes restrictions on data processing and consumer reporting and enhances the organization’s responsibility for storing and handling personal data. This is an important part of the legislation, and a data scientist should recognize its effect.

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Conclusion: There is no doubt that a Data Scientist is an evolving career. However, initially, a candidate may face some challenges. But at the same time, it will reward you with the best salary, long-lasting benefits, and comfortable incentives. Thus, if you wish to pursue a Data Scientist career, you should be aware of the trends mentioned above. You will surely make a profitable and satisfying career in Data science if you up skill yourself with the new technologies and extend your experience.