____________________________________________________________________________ Introduction
- We then added the three numerical rankings for each job to calculate its overall score.
- To emphasize jobs that tend to pay more, are likely to grow more rapidly, and have more
job openings, we selected the 50 job titles with the best total scores for each of the six
RIASEC types. Because 17 Artistic jobs also appear on other lists, a total of 283 jobs
(rather than 300) appear on the Part III lists, and they are the focus of this book.
For example, Accountants and Auditors is the Conventional job with the highest combined
score for earnings, growth, and number of job openings, so Accountants and Auditors is
listed fi rst in our “50 Best Conventional Jobs” list even though it is not the best-paying
Conventional job (which is Actuaries), the fastest-growing Conventional job (which is
Financial Analysts), or the Conventional job with the most openings (which is Offi ce Clerks,
General).
Why This Book Has More Than 300 Job
Descriptions
We didn’t think you would mind that this book actually provides information on more than
300 jobs. As this introduction explains, the jobs on the Part III lists are based on the SOC
job classifi cation system, but in Part IV we describe the related O*NET jobs separately.! is
means that although we used 283 SOC job titles to construct the lists, Part IV actually has a
total of 326 O*NET job descriptions.
Understand the Limits of the Data in
This Book
In this book, we use the most reliable and up-to-date information available on earnings,
projected growth, number of openings, and other topics.! e earnings data came from the
U.S. Department of Labor’s Bureau of Labor Statistics. As you look at the fi gures, keep in
mind that they are estimates.! ey give you a general idea about the number of workers
employed, annual earnings, rate of job growth, and annual job openings.
Understand that a problem with such data is that it describes an average. Just as there is
no precisely average person, there is no such thing as a statistically average example of a
particular job. We say this because data, while helpful, can also be misleading.
Take, for example, the way we assign the jobs to the six personality types. We follow the
ratings assigned by the O*NET database, which are based on analysis of the occupation’s
defi nition, core work tasks, types of knowledge used, and other information about the job.
But workers with the same occupation title often work in diff erent settings and have varying
work duties, use varying kinds of knowledge, and vary in other ways that should infl uence
the RIASEC type one would assign to their job. For example, Librarians who do research
for a corporation have considerably diff erent work tasks from the Librarians who work in a
