This post is contributed by Burtch Works’ data science & analytics recruiting team.
As anyone who has tried to discern the “true definition” of a data scientist knows, titles can mean different things to different people. A data scientist in one organization might be a predictive analytics professional in another, and a Director position in one company might be a Senior Manager position in another.
Title confusion of any kind can make the job searching process complex. How do you know what role you’re getting yourself into? How do you search? How can title confusion impact your career?
We wanted to talk about two different types of title confusion – seniority (Director vs. Sr. Manager, for example) and role (Data Scientist vs. Analyst, for example) – and how you can be cognizant of them when job searching.
There is no equitable translation between companies about what level of responsibility or management experience separates a Senior Manager from a Director from a VP. 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.
A company that is said to be “title heavy” may grant higher-level titles to positions that might not pay as much or have as many management requirements as a lower-level position at another company. 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.
Since titles are not standardized between companies (and industries), being overly-focused on titles can present problems when job searching. After all, the title may not necessarily mean what you think it does. The best way to overcome this is to carefully consider the role itself and look at:
- Who the role reports to (Director? VP? CEO?)
- Number of direct reports (management responsibility)
- Scope of the role (heading a department? leading a team?)
- Responsibilities (tactical? strategic?)
The scope of the role might be considerably larger than the title indicates, or it might be smaller. Titles can vary significantly, so take into account the whole package, including responsibilities, scope, compensation, etc. when evaluating opportunities, because these are the main factors that a hiring manager will look at when evaluating this role on your resume.
Title Confusion: Position
In recent years, the term “Data Scientist” has, to some, become a catch-all buzzword that encompasses anyone who works with datasets. 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.
Regardless of what your definition of data science (or analytics, or BI or IT etc.) is, it’s important to keep in mind that the companies you are applying to may not share your definitions. We’ve heard from many professionals that they’ve applied to data scientist positions only to find out that the role was not what they thought it would be.
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. Our best advice is to see if you can speak with a technical person and ask questions, so that your expectations are clear on:
- Tools used and methodologies employed
- Types of data
- Where the data is coming from
- Whether the data is unstructured vs. structured
- How much time is spent on analytics/analysis vs. data management vs. other tasks
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. It goes without saying, but before searching you may also want to think about what exactly you are looking for!
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Want to learn more about data science and analytics career planning? Watch the webinar recording below to hear our recruiters’ best advice on interview preparation, tools and skills to learn, salaries, and more!