Technical Skills Every Data Scientist Must Have
The recently emerged field of Data Science, has rapidly becoming the most sought after, career option in the short period of time, since its inception. There are so many people, both from technical as well as non-technical background that are drawn to this filed and rightfully so. The main reason why this field has amazing future prospects, is mainly because our entirely world, today has begun to run on data and it various other nuances. So for all those who think they have the right kind of mindset, the suitable likes and dislikes and traits for becoming a data scientist, it is also important to have certain technical skills. The shape that the field of Data Science has taken today, the professionals working in here, are very much expected to be well versed in the use of popular data analytics tools. These tools are what enables the data scientist, to carry on their work with finesse. They are namely, R Programming, SAS, Hadoop, Java, Python, SQL, Hive, Pig and so on. While having the nontechnical skills like visualization, unearthing hidden patterns, trying to look beyond the ordinary count, but these professionals are expected to have a strong technical skills set, if they wish to make it big in this industry. Here’s a list of technical skills, that every Data Scientist is expected to possess Math and Stats The very basic requirement of a Data Scientist, is the knowledge of R, SAS and strive to recognize patterns in huge data sets. As it is data sets that are being dealt with here, having a strong background in statistics, maths, algorithms and machine learning; becomes of utmost importance. Domain Expertise
If you are a data scientist, working in a particular domain, say for example retail, then it becomes of utmost importance for you to have, thorough knowledge about your domain and business. This should not just be about a particular aspect about the domain that you work it, rather it should be a knowledge, which is spread across various divisions of your firm, namely, marketing, sales, distribution, supply chain, operations, pricing, finance and so on. This knowledge is usually acquired by being uber curious about anything and everything that your company does. Programming Expert It is of utmost importance for a data scientist to be an expert at programming. It is not necessary for you to belong from a compute science background for the same. Regardless of your area of education specialization, you must be comfortable programming various languages, which include Python, Java, C++ and so on. You need to be able to examine all of the software packages, find the right software package for yourself, be able to run it as well as be competent enough to make any changes and modify it as per your requirements. Sometimes a Data Scientist is also expected to design and develop computational techniques, just for solving business problems. If you do happen to belong to a nontechnical background, taking up a course of certification in the various data analytics tools is the best bet. Imarticus Learning, offers industry endorsed courses in tools like R Programming, SAS Programming, Hadoop, Python, which will help you develop those much needed technical skills to make it big in this field.