At the root of Data Science is the need to use data in order to ascertain certain information and answer certain questions. Businesses that either possess data or are looking to collect data, need data scientists and those data scientists need a few different skills up their sleeves. We have put together a list of the top skills to look out for in the data scientists you are hiring in 2021.
Data Visualisation and Wrangling
If a company has mined or acquired data, which is not readily useable, it must be made useable. Raw data must be wrangled into a form that can then be understood, processed and modelled. This can be done by combining from multiple sources or cleansing the data of its mistakes and impurities. Once these actions are performed, it allows data professionals to analyse the data, confident that it is accurate. Figuring out what the data is telling them is another challenge that data scientists routinely face and visualisation helps two-fold. Firstly, as a means of them learning from the data and understanding what it has to tell them. Secondly, it helps them craft a narrative around, say, consumer behaviour, using visual graphics (with charts, maps, etc.) to communicate and convince the management.
Stats and Probabilities
The use of mathematic systems to decipher and decide what data to use and how to use it, is an important factor and your prospective candidate will need to be a maths whizz. This doesn’t just count for known numbers, but they must also be able to adequately estimate unknowns from knowns too. Statistics are usually based on probabilities so the two go hand in hand. Trends and dependencies can be identified using stats and probabilities which can aid in future planning for the business via data modelling. Patterns can be identified and problems can be predicted.
An understanding of Cloud and Cloud Computing is incredibly important to data scientists in 2021, as it means they are able to access databases and tools on platforms from Google, IBM, Windows and Amazon. Access to huge amounts of data resources helps the data scientist mine, acquire, wrangle and analyse data much quicker than via traditional methods. Modelling and optimising performance are also made easier via the cloud, and savings in time, mean savings for your business.
Multivariate calculus is an important skill within machine learning due to the use of unknowns and predictors. It is used in such areas as gradients or plotting and values for functions such as sigmoid, step, vector or cost. Matrix algebra and neural networks also come into play.
Software and Programming
Python is usually the major language you find data scientists working with, but of course there are many to choose from, including Java, Scala and SQL. Python is usually chosen as it is kind of a ‘one-size-fits-all’ contender. It will come as no surprise that programming is important within data as it covers a lot of skills which are integral to create useable data and deal with it.
Yes of course that perfect candidate will have a lot of skills and one of the most important is the ability to define, store and index that data for ease of retrieval and use. Expertise within requesting and file structure will help your candidate cut through to what they need in order to test and manipulate it.
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