What to make of a failed job interview?

Some of you may remember that I had started a series of blog posts titled “What I have learned about landing a job in tech” to share my personal experience about interviewing with top tech companies. I promised to write four parts but actually published only two: About the importance of differentiating yourself and being a marathon runner. Well, it is a shame that it was 1.5 years ago and I am yet to complete the series. Better late than never, and here we are with Part 3!

In this part, I will be discussing how I think one should interpret an interview failure (and indirectly, a success). I find this topic important because any negative interview outcome used to overwhelm me, shake my self-esteem, and prevent taking the right lessons that would help me improve. In retrospect, the reverse was also true: I probably overestimated my success in cases of positive outcomes. I am hoping to convey my learnings, not only from my many failures (see the second post in the series to get a sense of how many) and some successes, but also from my experience as an interviewer over the past several years at different companies.

A necessary disclaimer before I start: What you will read in this post are completely my personal views and not (necessarily) those of my employers (current or previous). Fortunately, companies and organizations go to incredible lengths to ensure their standards are reflected in the hiring process and the outcome is a collective decision of a diverse group of individuals. So, even if my take is incorrect in some respects, there are always a bunch of other people along with a concrete process to correct me when it comes to specific decisions.

After this long of an introduction, here are what you will read in this post:

With that, let’s dive in!

“We have decided to move ahead with another candidate who we feel is a better fit for this particular role.” For long, I felt pretty annoyed by the “politically correct” and “kind” narrative of the “right fit.” Back then, I was taking those outcomes as comprehensive assessments of my entire set of skills and accomplishments and my response to such sentences in my mind was more like “yeah, tell me like it is. I am not good enough!” Oh boy, was I wrong!

Sitting on the other side of the interview table over the past several years has given me the chance to review many resumes and meet many candidates, all of whom had nothing but a lot of hard work in their past and amazing portfolios! Great degrees, online courses, personal projects, past experience… None of us should underestimate the effort that goes into each of those lines on our resumes!

Yet, without a doubt, a rejection is a disappointment. One cannot help but ask “why”… “What happened?” What happens is the following:

This statement may sound trivial, yet it is not, and it is important to unpack it.

As an interviewer, there were many cases when I wished we could open a role for a specific candidate, who, unfortunately, was not the best match for what we were looking for at that moment. Similarly, many instances when I wished we had more headcount to hire more than one of our candidates. Having said that, in all those cases, I felt comfortable that those candidates would land great jobs with some other team/company anyway because of their great work and background.

Let’s say there is a role you are really interested in and focused so hard to get an offer for. Imagine that as you exit the building at the end of the interview day (or close the Teams/Zoom session, as is the case nowadays), an oracle appears in front of you and tells you that you are the most qualified candidate and the best fit for the role. Now you are confident that you will get the job. Several days later, you get a call from your recruiter, and… those words… “another candidate who is a better fit…”

In your eyes, it is obvious that the interviewers made a mistake. Did they, though? Or, how big of a mistake was it?

Now, let’s hypothesize that the only way to truly find the best candidate in the pool is to have the top three as probationary employees over a 90-day period, and only then the company can derisk missing the best match. Well, this is probably impractical and costly for most situations and what makes sense is to take the risk of slightly being wrong in the decision. As a result, as much as companies would want, the offer may not always go to the candidate who is the best fit for the role. Or, to put it less dramatically, it is a success for the company to hire one of the good fits for the role in the candidate pool, and some of the other candidates that don’t get the offer are perhaps equally right fits. So, if a candidate gets rejected, there is a chance that it was a close call, but the hiring mission was accomplished.

Now, the situation above was about failing to identify the best (or a good) candidate, i.e., a false negative. Another way the hiring decision could go wrong is to hire someone who is not a good fit, i.e., a false positive. This is usually considered a bigger risk because such an outcome would be bad for two parties: The team/company and the candidate (now the new hire). That would be a lot of waste of resources and reduced morale on both sides. In fact, in many cases, interviewers try to understand if the candidate would be happy in the role if hired. For example, if the candidate expressed their passion for publishing academic papers in their job and did not realize that it is not a focus for the role, the interviewers might conclude that, as good as the candidate is, their interests don’t match the role. Or, if it is a senior role and the candidate does not have enough experience, the expectations after hiring might overwhelm the candidate. Therefore, it is an important goal to avoid false positives in the outcome of an interview.

Now, as you may remember from your stats classes, striving to avoid false positives will come at the cost of increased false negatives. In simpler terms, as more candidates get rejected to be on the safe side, those rejections will have an increased number of good candidates. (But again, as long as the team identifies a comparably good candidate, the mission is accomplished.)

My apologies if I bored you with my efforts to tie the discussion to stats concepts (and unfortunately it is not over yet). But all I am trying to say is that it is a perfectly plausible (although not pleasing) outcome to get rejected from a role that you are a great fit for, and it is not necessarily anyone’s fault.

If you think about what an interview outcome is, in statistics terms, it is an estimation of a candidate’s fitness for the role based on a limited number of interactions (a sample) with the individual. When statistics are at play, it means there is noise, luck, false negatives, false positives, as mentioned already. It also means that if you repeat the interview (experiment) with different (or same) interviewers, questions, time of the day, day of the week, etc., there is a chance that the outcome will be different.

Just think about (some of) the variables at play in an interview:

And at the end, all this evaluation and ranking and conclusions are made by humans, who are, knowingly and unknowingly, subjective creatures in their decision-making (despite the best efforts against it); and their decision might be simply incorrect. If you want to learn how subjective we all are, check out Daniel Kahneman’s famous book “Noise.”

This section can go on with more examples of how the interview process is imperfect. But I feel I need to clarify my stance before I wrap up here: I am not in the camp of “the system is broken.” Quite the opposite: I think interview loops work quite well for the most part, as a result of deliberate efforts by companies. It is just that, like any other process in life, it has shortcomings and it is important to recognize that.

Much of my presentation so far aimed to give you a broader perspective about interviews than simply deriving misery out of a negative outcome or an absolute triumph out of a positive, as I often used to do. That is not to say that there is no lesson to learn in the former case or no success to celebrate in the latter. There absolutely is. And next, I will give my two cents about how to approach the process and those outcomes.

I hope you enjoyed this post and found it helpful. Thanks for reading.

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