Screening for Humility and Integrity (Hiring Series Part 3)
This is part of a series sharing what we've learned in more than 15 years of attracting and screening education data talent, and what it means in meeting the moment of today's hiring market.
Most hiring processes for data roles in education are designed around one question: Can this person do the analysis? That question matters, but it’s not the only important one.
The harder question is this: What happens when their analysis is wrong, incomplete, or inconvenient?
In education, the answer has real consequences. When uncertainty is ignored, when weak findings are defended instead of examined, or when results are shaped to fit expectations, the harm doesn’t stay abstract. It lands on children.
That’s why hiring data talent can’t stop at screening for technical skills. It requires screening for how people handle truth under pressure and how they respond when they don’t have the full answer.
In our experience, two qualities make the difference: integrity and humility. Integrity shows up as truthfulness when the data is messy, ambiguous, or unpopular. Humility shows up as the willingness to notice limits, admit mistakes, and seek other perspectives. Together, they determine whether a data professional helps an organization learn or quietly misleads it.
Since I joined SDP in 2016, my role has been to think not only about the analytic questions our partners hope to answer, but also about the roles our recruited candidates will actually play in answering them well. That means paying close attention to how candidates may interact with stakeholders and navigate uncertainty in real organizational settings.
Of course, we ruthlessly assess technical skills. Strong data analysis, statistics, coding, and visualization skills are all necessary. But technical skill alone is not enough. What matters just as much is how someone uses those skills in relationships with others, and what they do when data doesn't cooperate.