This is my first blog post
My Quick Take on the Role of Data Scientists
A data scientist must be familiar with all aspects of their organization, aware of the data it has, and able to communicate with stakeholders clearly to inform decision making. They must understand how to employ and how to value the tools at their disposal, whether the tool is a team member who can program or an application simplifying machine learning.
But to really hold the title of data scientist and be reliable and essential within one’s organization, I think it takes more than the traditional Venn diagram of math, computer science, and subject matter expertise. I think this visualization, and several job listings cited in the blog posts we read for this assignment, were missing organizational trust.
I think any employer giving an employee broad access to its data must be aware of the risks inherent in sharing this information. Whether it’s private medical details, financial transactions, strategic business plans, or military troop numbers, leaders have much at stake within the data they collect.
Data Science vs. Statistics
With apologies for my limited understanding of what statisticians do, I think we could fairly state that a data scientist is a statistician with a particular set of skills, including some programming. Kind of a special flavor of statistician! I do not believe, based on the articles I was assigned to read, as well as my own set of experiences, that a statistician necessarily has to be capable of data science. Computer programming and a level of expertise in a subject other than stats are not requirements to be a statistician, but are necessary for a successful data scientist. Perhaps a data scientist does not always need to have as great an understanding of statistics as someone serving in a statistician role. But a strong understanding of statistics certainly would make a stronger data scientist, able to more confidently find and explore questions and solutions through data.
Me
My perspective is, of course, formed through my own experiences. I don’t fit neatly into the data scientist or statistician bin at all. My background includes forays into military rotary wing aviation, leadership, economics (undergraduate), and (lately) operations research. (Side note: Operations research is another interdisciplinary field with a really squishy definition)
I find many of the hard skills I have studied in these fields are incredibly perishable and also time consuming. The impact of those qualities is that moving to a new field can prevent a person from considering themselves a member of a previous field, even when the areas seem complementary.
For this assignment, we students read through multiple articles/blog posts which sought to define a Data Scientist and distinguish it from similar career fields. Multiple authors cited the private sector demand for these employees; however, I noticed no one touched on the need for data science within government. But that is my only experience so far. I look forward to gaining more perspective this summer through the teaching and fellowship in this course.