Now that we have taken a look at the personal qualities required to obtain careers in big data, let’s turn our attention to some professionals who have them!
As mentioned in Section 2.2.2, there are many job titles in the field of big data. These jobs can range from data specialist to product manager [13]. One thing all of these professionals have in common is technical and math backgrounds, with a multitude of interests. It is important to note that big data professions are gender-neutral, as we will see in the following examples.
2.4.1 Jonathan Goldman’s Career Path
A good example about the breadth of skill requirements for being a Data Scientist is highlighted in the career history of Jonathan Goldman, Director of Data Science and Analytics at Intuit. In his interview with a fellow data scientist at Quora.com, he describes his career path as:
- Bachelor of Science in Physics at Massachusetts Institute of Technology
- PhD in Physics from Stanford
- Business Analyst at Accenture
- Data Scientist at LinkedIn, becoming the lead of Product Analytics team
- Co-founded Level Up Analytics, a data science consulting firm
- Level Up Analytics acquired by Intuit, where he became the Director of Data Science and Analytics
It’s clear that a data scientist can and should have backgrounds in various fields. Jonathan studied physics to a doctorate level and even co-founded a businesses before becoming a director of data science and analytics as he wanted a faster-paced career rather than continuing in the academic field [5]. He came to realize that he loved collecting and analyzing data during his master’s research because he could obtain results more quickly. Jonathan knew that he wanted a more technical career after accepting a job at a consulting firm [5]. He would become the first data scientist at LinkedIn where within only a couple of weeks he knew that this position was a perfect match [5]. He felt that the company was teamwork-oriented, and everyone enjoyed working together to achieve a common goal [5].
2.4.2 Other Interesting Professional Career Paths in Big Data
Rosalyn Ku, a math major learned about data analysis at a career fair, and the company Factual sparked her interest at this event almost instantly [13]. Her job as a data specialist is to organize sloppy data from online environments and make it useable for other organizations. This job permits her to be involved in the coding world along with collecting and analyzing data.
Brittany Reye, is a research associate at Basis with a degree in psychology and history with a focus on neuroscience and research. She said that this allowed her dream of “objectively quantifying the human experience” to become a reality [13]. She is a research associate at Basis, where she works with wearable technology. This specific technology obtains data with which she is constantly interacting to enhance the prospect of wearable technology.
Nikita Lytkin, a lead modeling scientist wanted a challenging career that would permit him to solve difficult and complex problems [13]. Working for Quantcast is the perfect fit for him because not only is he challenged, he is also given appropriate resources that allow him to be successful in his chosen profession. His focus at Quantcast is in advertising, and he works with a large amount of data [13].
All of these professionals have many different backgrounds and are seeking a challenging career with endless possibilities. One of the basic prerequisites to start a career in big data analytics is to have a genuine interest in data itself.