On Hiring Data Translators: Lessons From My Seven-Year-Old Mandarin Teacher (Hiring Series Part 5)
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.
My daughter started learning Mandarin this year. For a while she was deeply interested in hieroglyphics, so this feels like a practical pivot.
Lately she likes to play “Mandarin teacher.” She seats my partner and me on pillows on the floor, points to different characters on her white board, and asks us to interpret them. She is animated and completely certain she has been clear.
I, meanwhile, am completely lost.
When we answer incorrectly, she grows very frustrated with us. In her mind, she has explained it. The meaning is obvious. Why aren’t we getting it?! She keeps insisting we try again.
Sitting there, looking at symbols I cannot yet decode, I sometimes think that this must be what it feels like to sit through a data presentation filled with unfamiliar terms and unspoken assumptions. Should I pretend to understand? Will I tune out? Will I give up and leave before things get heated?
Data leaders rarely have the authority my daughter has in those moments. They cannot insist the audience try harder. If anything, the burden runs in the opposite direction. But what I’ve come to realize is that data is a kind of literacy. What I mean by this is that understanding cannot be assumed, meaning must be constructed, and responsibility for clarity rests with the communicator. Literacy demands that we meet people where they are. If people cannot interpret what we produce, the analysis does not matter. That belief shapes what we look for in data talent.