The Impossible Job of Finding a Job
The most challenging part of college had nothing to do with actually being in college. Instead, it was finding a way to use the value gained after spending tens of thousands of dollars. That is finding a job.
It is a seemingly increasingly popular roadblock that college graduates find themselves encountering. Including myself. Now to be clear, it is not difficult to get a job.
I could walk down the street to any restaurant or service-based industry and get an entry-level job. The problem is that those jobs do not use the skills I gained in college.
So to rephrase, the most difficult part of college is finding a job that is in your field, uses your education, and pays close to your estimated expected value. The problem is that even entry-level jobs in your field require experience to be considered for the position. But that’s the catch. How do I get experience if every job requires experience?
Frictional Unemployment
This has always been a problem. It is called frictional unemployment. It typically refers to workers who are in between jobs but also applies to workers looking for their first job.
Frictional Unemployment is caused for a few reasons. One is because people are switching or changing career paths, or in my case starting their career. Another is that workers can’t find the employers hiring, or employers hiring can’t find the people who are willing to work.
Switching or changing career paths is good and shows signs of a healthy growing economy. This leads us to two conclusions. That 0% unemployment is impossible and that we should strive for some unemployment. A healthy economy requires some unemployment. Similar to how we don’t want zero inflation, but also don’t want hyperinflation. A small reasonable amount for inflation is healthy.
Websites like LinkedIn have created a space to limit the amount of frictional unemployment. It does this by making it easier for employers to find workers and workers to find employers. The concept is great and it does a decent job. Yet there is still a lot of unnecessary frictional unemployment.
I think the task Linkedin took on to reduce frictional unemployment was more difficult than they thought. For one, companies when vetting employers look for various different things depending on the position. So just a profile with a resume isn’t going to cut it. In fact, it is typically better to apply on the company’s website rather than through LinkedIn. Which makes the application process a bit more difficult.
Another problem is the resumes themselves. Resumes now go through a computer screening before it even reaches human eyes. So someone perfectly qualified for a job might not even be considered because a computer didn’t like the formatting or wording of the resume. This creates more frictional unemployment, not less.
The biggest reason Linkedin is not the frictional unemployment buster it should be is that if it was, it would be boring. Linkedin is more of a social media platform than a job-matching website. It’s the Instagram of work. This is fine, the people enjoy it and Linkedin makes money, win-win. I just think we need to throw out the idea that Linkedin is this job-matching paradise.
My Applications
Here is a SankeyMATIC diagram of the all applications that I submitted. Almost all of these applications were for jobs that I found on Linkedin or other job-finding sites (Indeed, etc…). I applied to jobs in my field of study: Data Science, Data Analyst, and Business Analyst. Location was typically out west to either Colorado, California, Washington, Arizona, or Texas.
The vast majority of my applications were cold calls. I just straight up applied on the company website with my resume with no reference. This didn’t really go over too well as I only offered an interview for 5 positions out of 154 cold applications (3.2% success rate).
The jobs I applied to where I had a contact at the company I got an interview for 4 out of the 5 positions (80% success rate). It is clear how important having a contact is to get to the next step of the hiring process.
Out of my 9 phone interviews I received a call back for a second interview from 4 companies. And out of those 4 interviews I was offered a job at 2 different companies. One of which I accepted at Santee Electric Cooperative Inc. in South Carolina as an Information Systems Analyst – Data Analyst.
One thing to note is that 2 of the positions that I was able to get a second interview for were jobs not in my desired locations listed above. My thinking is that applying to high-density/high-demand areas is much more difficult to get an interview never mind a job. Simply because of the mass amounts of people who live there and the people wanting to move there (i.e. me).
So my overall success rate for securing a phone interview was 5.6%. Although it looks to be skewed higher since having a contact at the company increased my odds of getting an interview.
Also, note that my data set is N = 159 so not very large. I’m not trying to predict anything with this data, it’s just something too cool to look at.
Success Rate
My success rate of getting a second interview is 44%. And a 50% chance of being offered a job if I got a second interview. Or a total of 1.2% of receiving a job offer. Not very inspiring after getting a college degree.
The other job offer I received I was hesitant to even put in my data set as it is an outlier compared to my other applications. One, I had a reference for the job. Two, it wasn’t in Data Science or anything relating to my field. Three, it was an Adventure position in which I have experience in and my reference is a well-known contributor in that field. Four, it was a low-paying job in a less desirable area, at least for me. Not to sound cocky or arrogant but I would have been surprised if I wasn’t offered the position.
So that would bring my job offer rate in the data science field to around 0.63% if I removed that application from my data set. But according to the law of large numbers, if each application is independent of one another. And if the probability of getting a job offer is 0.63%. After 158 applications the probability of getting at least one offer is 63.3%. And after 1000 applications I have a 99.8% chance of getting at least one offer.
It feels damn near impossible to find a job and yet everyone is hiring. In fact, what was very surprising is not that I got rejected by 79 companies but that 78 ghosted me, with no response whatsoever (which happened 49.3% of the time). Why would you announce that you are hiring and yet not even respond to your potential employees?
No More Jobs
Another interesting point is that I received a lot of notifications that the company is “no longer offering this position”. Meaning that not only did I not get the job but no one did, as there is no longer a job. Unfortunately, I don’t have the data on it. But it was from more than just one company. This makes sense as we saw huge layoffs in the tech sector recently. Typically at the big tech companies like Twitter, Meta, Stripe, and Lyft. But this trickles down quite quickly to any tech position in any field.
My thought is that layoffs occurred during covid. Businesses realized that they can run just as well with fewer workers. So these positions they were initially hiring for are gone because they don’t actually need them. So they remove the listing. Now, these companies are looking at their current staff to see who else can they get rid of and the business still runs just as smoothly. Hence the recent layoffs.
Regardless I am lucky to finally secure a job in the field I want and let’s hope in the future we can reduce frictional unemployment even more. The moral of the story is to just keep applying and eventually you are guaranteed a job.