AI News, There’s No Such Thing as a Data Scientist
There’s No Such Thing as a Data Scientist
There’s a memorable scene in Office Space where consultants determining employee productivity start by asking, “What would you say… you do here?” That scene and the “What I Do” images are funny because we empathize with the struggle to describe our jobs.
This post takes advantage of Indeed’s tremendous amounts of behavioral data to describe trends in the field and more specific definitions for data science roles.
Even earlier in 2012, a much ballyhooed article called Data Scientist the “Sexiest Job of the 21st Century.” If the title alone isn’t enough, maybe folks are interested for monetary reasons.
Our colleague Trey Causey wrote about the convergence between product managers and data scientists in the “Rise of the Data Product Manager.” Many of us at Indeed also felt that the title “data scientist” has recently become more of a catchall for many different sets of responsibilities.
For this analysis of job titles, we looked at all site visitors who entered the search query “data scientist” on Indeed for the month of January 2018.
We calculated the cartesian product of these matrices to show the frequency between any pair of search terms: Next, we removed “data scientist” from the data, as this search was present for all users.
According to the igraph documentation, “this function implements the fast greedy modularity optimization algorithm for finding community structure.” While researching this algorithm, we learned that it was designed to quickly create communities from large data sets that have sparse regions.
You’ll have to read that paper to understand what it means Next, we wrote a function with a pruning parameter to choose the minimum number of vertices in each cluster.
This parameter is best set by “guess and check”, as higher numbers don’t necessarily mean more total groups and vice versa.
This tells us that job seekers who search for business intelligence might be looking at a wide variety of other jobs within the data science realm.
From searching patterns we’ve observed, if someone were to say, “I want to be a data scientist at Indeed,” it could be unclear which team or title would be the best fit.
The Data Science Industry: Who Does What (Infographic)
While a data driven approach is finding its way into all facets of business, companies are fiercely fighting for the best data analytic skills that are available in the market, and salaries for data science roles are going in overdrive.Companies’ increased focus on acquiring data science talent goes hand in hand with the creation of a whole new set of data science roles and titles.
Furthermore, we look at the top employers that are currently hiring these different data science roles and how the average national salaries of these roles map out against each other.Hopefully this infographic will help you to better understand the different job roles that are available to data passionate professionals.
How to Manage Title Confusion in Data Science and Analytics
You may have discovered in one of your job searches that roles with the same number of direct reports can be titled completely differently, and positions with the same title might have wildly different pay scales at different companies.
It’s important to keep in mind that if you are at a company that is title heavy, then your title may move backwards when you decide to make a career move, even if your responsibilities increase and your career moves forward.
The best way to overcome this is to carefully consider the role itself and look at: The scope of the role might be considerably larger than the title indicates, or it might be smaller.
For others, including Burtch Works, there is a set definition of data science that is separate from other fields like predictive analytics, business intelligence, operations research, and IT.
Depending on whether your contact is a technical manager or human resources professional, your initial contact may not be as familiar with the nuances of the position, so they might not be able to clear up any confusion for you.
Especially as areas like predictive analytics and data science continue to blend, it will be very important to read carefully and ask questions, to make sure that this position is actually what you’re looking for.
- On Thursday, October 17, 2019
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