In a world dominated by big data, it stands to reason that many organizations are eagerly seeking out the best data scientists. With all this high demand, data scientists now have their work cut out for them to truly stand out from what is an increasingly crowded field. While it’s true that finding a data scientist job is not the most difficult task, it’s up to each individual data scientist to prove themselves. That means being the best at what they do and showing why they deserve a highly sought after position. With this in mind, data scientists can help themselves out tremendously by adopting certain skills and talents that will help differentiate them from others in the same career.
While it might not come as a surprise that data scientists need to know their way around computers, it still needs to be said that programming skills are an absolute must if they want to truly excel. Some data scientists can get by with only rudimentary understanding of programming techniques, mainly devoting themselves to viewing and analyzing the data that is collected, but for data scientists that want to get to the next level, they need to be able to manipulate that data as well. Programming skills give data scientists more control over the data collection and analysis process. At the same time, they can increase their worth by learning and mastering multiple programming languages such as SAS, R, Python, and many others.
While programming skills can certainly be valuable, data scientists can do harm to themselves if they ignore the business aspect of their careers. Every data scientist should take the time to develop business skills depending on the type of company they are working for. This includes gaining detailed knowledge on how the businesses they are in work and what role they play in improving them. Those with business knowledge will be able to work more closely with company executives. They can also show a greater level of dedication and interest in the success of a business. Developing the right blend of business skills often requires extra work, such as attending training sessions and reading up on company material. All that hard work can pay off in the end though.
Of equal importance is the development of excellent communication skills. Big data analytics can be a complicated and complex concept for the layman to understand, so it’s up to data scientists to possess the communication skills necessary for those within the business to grasp how it can be used and the roles big data can play. Data scientists need to learn how to translate findings from big data analytics into how it meets specific business needs. Many executives won’t care much for the minutiae of analytics tools, and much of the big data jargon will simply fly over their heads. Framing big data in its impact on marketing or sales, though, makes it that much easier to understand. Talking about big data is only part of the equation, however. Data scientists also need to learn how to listen to what the business side is saying and learn how to meet their expectations.
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Data scientists can also show their increasing value by demonstrating a desire to learn and grow. Intellectual curiosity is always looked upon positively, and this can extend not just to getting to know more about business but about data processes as well. The average data scientist will look at data on the surface and use it, but the data scientist that wishes to stand out will always look deeper into the data, finding new patterns and trends that may be missed by only casual observance. Data scientists seeking to improve this skill will be best served by keeping an open mind about big data analytics and always going one step further than might be required.
When all is said and done, data scientists that take the time to develop added skills and talents will find themselves head and shoulders above their peers. Some data scientists may even become tech experts within their own companies, with people coming to them with questions ranging from what is flash storage to the finer details of big data analytics and cloud computing.
Right now, data scientists find themselves in an envious position where their skills are in high demand while their numbers are in low supply. It won’t be this way forever, though, so they need to work now to gain the skills that put them at a different level than the rest.
Rick Delgado- I’ve been blessed to have a successful career and have recently taken a step back to pursue my passion of freelance writing. I love to write about new technologies and keeping ourselves secure in a changing digital landscape. I occasionally write articles for several companies, including Dell.
(image credt: Davidlohr Bueso)