How we learn to handle rejection in the job search can be transformative for our professional careers. Guest contributor Scott DeGeest breaks it down as a data professional.
As we start up our data science careers and begin hunting for jobs, we often discover the need to master rejection.
And, although this post focuses specifically upon rejection during the job search, many of those lessons apply to later stages of professional growth, too.
After all, if we handle rejection well, we’re better positioned to develop the persistence necessary to succeed in work and life. Or, in the words of RuPaul, “Failure allows you to find the places you had no idea existed.”
Job rejections often have little do with us, actually—especially in the latter rounds of an interview.
Getting rejected from an initial round of an interview is easy. It happens often. If you are applying for competitive positions, it probably should be happening as you work your way to finding the ideal fit.
Getting rejected in the latter rounds hurts more. That said, those rejections often speak less about one's skills set and more about the internal political dynamics of an organization.
Let’s look at it from a systems POV.
Most companies lack an effective system to hire people, which leads to both false positives (e.g., an employee with 3 years of data science experience who learned little on the job) and false negatives (e.g., an employee with less than a year of experience who studied in the evenings and learned a ton).
As a data professional, you know about these classification concepts. The concept I focus on here is recall, which is the ratio of true positives to the sum of true positives and false negatives.
Companies rarely strive to identify all true positives. Really, most have systems designed to get just enough positives (true and false!) to meet a benchmark, then they stop. Such a process leads to lots of false negatives and consequent low recall.
The conceptual takeaway here is that organizations constantly miss qualified candidates due to their own processes, and it's not on you to blame yourself for their inability to hire well.
Always practice and prepare for interviews, recognizing that the only levers an applicant controls in the applicant process are:
If you’re confident that you were prepared for the interview and meet the qualification minimums, squarely place that rejection decision as a shortcoming in an organization’s leaky hiring process, not your lack of skill.
This belief will help you sleep better and manage the job-seeking process.
Agility — combined with emotional intelligence and authenticity — can be key to transforming professional obstacles into opportunities, as research published in the Harvard Business Report revealed.
Rejections hurt because they evoke disappointment.
For example, a few weeks ago I put in a bid to do some data science contract work. Although I did not get a formal rejection, I learned through social media that someone else won the contract.
There are lots of reasons I may have been rejected. For example:
I spent about 24 hours letting myself be bummed about it. I gave myself some time to feel and process my negative emotions: “I worked hard! I am very good! HOW DARE THEY!”
Once I was done with those feelings, I knew I would rather spend my time reframing my experience in a productive way. I asked myself a few questions:
Feeling bad is sometimes part of the process. Let yourself feel bad, then move toward positive reframing when you are ready.
Rejection is a hard mental experience to process.
As such, reflecting on how you experience it gives you an opportunity to master how you respond to professional setbacks. To excel, you need effective emotional regulation tactics for processing these feelings.
Some options for regulation you can try:
Create your rejection catalog — a set of stories about people you admire getting rejected and failing — to remind you that greatness getting rejected is part of the process.
Set up a process for yourself to work through your feelings of rejection and failure.
Learning to handle rejection may be uncomfortable, but it need not overwhelm you. With the right perspective on the situation, it can help you grow and develop as a data professional.
Another factor that can make a difference, especially for people from groups historically underrepresented in the data field? Developing relationships with professional mentors who recognize your talent.
According to the aforementioned HBR story, having someone in your field to discuss the challenges of entering and succeeding in one’s chosen profession can go a long way to fostering success.
Fortunately, for Fellows and Alumni of Correlation One’s DS4A data training programs, mentoring is baked right into the talent development process.
And if you’re an accomplished data professional who would like to help develop rising talent? Then visit our Enterprises page to learn how we help companies like yours do just that.
Guest contributor Scott DeGeest, MBA, Ph.D. is a Community Advocate for Correlation One’s DS4A program. He also works as a Lead Computational Social Scientist with Interos, a tech company specializing in AI-powered supply chain risk management.
Scott would like to acknowledge William Johnson, Omolola Akinsehwina, and Keanu Renne-Glover for their constructive feedback on earlier drafts of this post.