Dr. Tajuddeen A. Williams

Choosing A Professional Role

· Personal Essays

For the past 17 years, I have been involved with computers and information technology professionally. When I chose my degree program, I did so on the basis that I would still be involved in IT in some form or another. After all, it has taken a long time to build my reputation as an applications developer. It’s for this reason that I will utilize my degree to benefit myself in something that is at the crossroads of psychology and IT. On my journey towards my Ph.D., I plan on taking on the role as a data scientist. The knowledge and understanding that I have gained in the realm of statistical analysis and the understanding of how statistics play a role in data collection is key to this field and it is something that studying psychology prepares you for.

Over the past 10 years, data science has become a field that is very high in demand. It’s been called the sexiest job of the 21^(st) century (Davenport & Patil, 2012). There are more jobs available than there are people able to fill the positions. The reason for this is understandable. With the skill sets being so diverse, it’s not an easy field to get in to. Data science, in general, is the extraction of knowledge from data (Davenport & Patil, 2012). Data scientists employ various tools in the analysis of their data, including SPSS and the R programming language. Psychologists are not taught computer programming as part of their degree program, which is one of the issues of getting into the field of data science. However, the same can also be said for people with math degrees who want to pursue the same field. For this reason, I have also taken courses at John Hopkins University that give me a background in data science and R.

Data science interests me primarily because it’s it deals with raw data. I can take what I already know about computer programming and apply it to that field. With computer storage becoming cheaper over the years, big data has been an area of interest for many companies (Waller & Fawcett, 2013). Companies are able to gather and store large amounts of data without breaking the bank. Since they’re able to store this data, they need someone to analyze it. In order to be successful in this field, data scientists need psychological insights in order to be able to tune customer analytics. Even at the undergraduate level, statistics courses are helpful for preparing psychologists for the quantitative and analytical requirements of big data science.

The data scientist does not just want to tell you about your data, they want to build things. It’s from building things that allow them to become and expert in their field. The term data scientist was only recently coined around 2008 (Davenport & Patil, 2012). Being able to network and continuously learn about the field is key to being successful (van der Heijden, 2002). Data science, even in its infancy, is constantly changing. Networking is huge in data science because of this. The Hadoop World Conference has not only become a social networking zone for data scientists to get together and test their knowledge, but it has also become a recruiting ground.

Even though it is a relatively new profession, post-secondary institutions are recognizing the need for formal education and have been responding by providing curriculum that teach these new skills. In 1963, the half-life of an engineer may have been 5 years, but in this rapidly changing field, it is more like 2 (van der Heijden, 2002). It takes a lot of studying and information gathering in order to become an expert in this field. The cost of staying up to date on the latest and greatest in any field is generally high (van der Heijden, 2002). However, there are a lot of free tools and courses that teach what is needed to know. One cheap alternative to attending a university is Coursera, which provides a certification course in data science.

Data science is a field that is not specific to psychology, but uses psychology. It will take a great deal of hard work in order to be an expert (van der Heijden, 2002). Those who have been working in psychological science or in big data already have a foot in the door. In order to gain these new skills, a person will have to take the initiative and learn on their own by employing an entrepreneurial approach (van der Heijden, 2002).

Data science isn’t necessarily a young field. The title is young. The work has been done for ages for those companies who could afford it. It is used it just about every field one can possibly think of, including medicine. It’s important for people to use data to make predictable analysis even in the field of sales. But data tells us a lot. It’s a lot more than just doing A/B testing. It requires that people understand the data in order to make inferences off of it. Psychology is suited for it. Even though I have yet to complete my program, for the simple fact that I have had to take statistics and I have a background in computer programming, recruiters have been reaching out to me. At my current job, they are taking advantage of my ability to do statistical analysis by allowing me to analyze raw data and present it in a way that they can take advantage of it. In this case, it happens to be the web and membership logs, and it lets us know where to gear our development efforts next

References

  • Davenport, T. H., & Patil, D. J. (2012). Data scientist: The sexiest job of the 21st century. Harvard Business Review, 90(10), 70–6– 128. ↩1 ↩2 ↩3
  • van der Heijden, B. I. J. M. (2002). Individual career initiatives and their influence upon professional expertise development throughout the career. International Journal of Training and Development, 6(2), 54–79. http://doi.org/10.1111/1468-2419.00150 ↩1 ↩2 ↩3 ↩4 ↩5
  • Waller, M. A., & Fawcett, S. E. (2013). Click here for a data scientist: Big data, predictive analytics, and theory development in the era of a maker movement supply chain. Journal of Business Logistics, 34(4), 249–252. http://doi.org/10.1111/jbl.12024 ↩

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