Data Scientist Skill Standards
The Center created a set of skill standards (critical work functions and key activities, with references) for the occupation of Data Scientist. The methodology included reviewing the Occupational Outlook Handbook, O*Net (courtesy of the Bureau of Labor and Statistics), and ran an EMSI report for job postings in Data Science to identify key responsibilities.
What are Skill Standards? Skill standards tell us what a worker needs to know and do on the job and how well he or she needs to perform to succeed in the workplace. Skill standards define both the work itself and the worker qualifications, specifically the skills and knowledge required to successfully perform the work.
How do skill standards benefit community and technical colleges?
Skill standards can help community and technical college instructors address the following kinds of issues:
- How to determine the content of technical programs
- How to know the most current skills and knowledge to teach that will get students jobs
- Getting employers to define specifically the skills and knowledge they are looking for in employees—and how well potential applicants must perform to get and keep a job
The purpose of skill standards is to document the skills, knowledge and performance standards that employers require in their workers and to communicate that information to education and training providers, such as community and technical colleges. Community and technical colleges can then use the skill standards to develop curriculum that meets the needs that employers have identified.
Element 1 – Defining Critical Work Functions
First, skill standards break down an occupation into its principal responsibilities or critical work functions (CWFs). CWFs should identify the highest or broadest level in the hierarchy of work responsibilities; these are the work functions required to accomplish the key purpose of the occupation as it is defined in the rationale for selection of occupational area form.
Element 2 – Defining Key Activities
To accomplish each CWF, a worker must perform several steps or tasks. The relationship between CWFs and key activities is one-to-many: One CWF contains many key activities.
A key activity is typically written as a behavioral statement with an action verb. For example, “Inspect sample parts and prepare reports on parts compliance” would be a key activity.
When defining key activities from raw data, keep in mind that there are usually 3-6 key activities per CWF. This may require aggregation of tasks or the addition of a CWF that more accurately categorizes the activities. (Source: Developing Skill Standards: A User’s Guide, 2015)
The Center then took the Data Science skill standards and had an IT professional focus group at the end of March 2019 (software engineers, software developers, data analysts from companies like Microsoft, Facebook, and Amazon) to review and provide feedback on the Center’s work product.
The skill standards underwent a final revision based upon the IT professional focus group. Please contact the Center for a copy of the Data Scientist skill standards. firstname.lastname@example.org