In order for anyone to become a data scientist, five skills are essential. One is domain knowledge where the person needs to be aware of the field in which he/she will be applying data science concepts and processes. The second is machine learning or simply programming capability which refers to programming skill and knowledge of the basics of computer science concepts. This skill is considered essential since data scientists work with large volumes of complex data that cannot be deciphered manually or by using non-digital technologies like statistical theories. The third is creativity by which aspiring data scientists need to be able to apply data science techniques to problems or modify programming codes to suit a particular requirement. Understanding of business outcomes is also necessary to be known by a data scientist because he/she needs to know for what they are analyzing and interpreting data. Finally, interpretation of data is important too because without being able to understand and give meaningful definitions to the data analyzed, data scientists won't be useful.
IT professionals, computer science graduates, and professionals who possess experience in programming are at an inherent advantage when it comes to becoming a data scientist. This is because of their knowledge of programming language. Even if they don't possess other skills, knowing how to code in a programming language can be transformative when joining this field. Each business problem or marketing strategy requires different solutions. Programming languages are flexible and can be coded in different manners to adapt and provide different solutions.
As more companies make the shift to change their business approaches to one where data analytics and data science in general plays a bigger role, more data scientists will be required. Since data science in the context of big data analytics is relatively new, there isn’t enough data scientist who is experienced in programming. Hence, there is a rising demand for experienced programmers who can also double up as data scientists. Being an analyst is different from a data scientist. An analyst may just scan large volumes of data and pick out blocks of data that have some relation to the search criteria. Data scientists need to be more discerning in what they pick and programming skill helps in this aspect since the data scientist can code a program which focuses on extracting specific information from large unorganized big data.
In spite of the above, experienced programmers are not simply recruited without any skill addition. Usually, companies prefer to recruit programmers who already possess an advanced degree like a Masters or a Ph.D. that is related to computer science. Advanced degrees related to mathematics or statistics are also welcomed but require programming skills, in addition, to being considered on par with computer science graduates. Another way to get skill addition is to go for advanced certification programs like those offered by Coursera or Udemy. Data science boot camps like Microsoft's DS3 summer school and NYC Data science academy offer a way for those unfamiliar with data science to get acquainted with the subject and be employable. Companies also offer in-house training modules for their programmers to become data scientists. Apprenticing under senior data scientists is another option for an experienced programmer to become a data scientist but is not very feasible compared to the other options.