explaining your job is a data storytelling opportunity
“What do you do?”
It’s one of the most common questions we ask in casual conversation. It’s also one of the trickiest to answer—especially if your work involves data.
I learned this the hard way early in my career.
At that time, I worked in banking in Credit Risk Management. When someone asked what I did in a social setting, I’d respond with, “I’m a credit risk analyst.”
This was a guaranteed conversation-killer. I don’t think people were trying to be rude. It’s just that most people don’t have a mental model for what that title means. In the absence of understanding, the brain does the most efficient thing it can do: it moves on.
Looking back now, what I was doing was the professional equivalent of showing up to dinner and saying, “I’m a Level 3 wizard in the school of quantitative uncertainty.” It’s accurate—but not super helpful. It wasn’t because the role wasn’t interesting. It was meaningful work. But I didn’t know how to explain it.
Later, at Google, I figured out why.
Your job title isn’t your job
Many job titles are designed for internal systems—org charts, hiring ladders, compensation bands. They aren’t necessarily intended to help another human being understand what you do. Titles are shorthand for insiders. To everyone else, they can feel like jargon, ambiguity, or worse: an insurmountable wall.
Even today, in the analytical world common job titles can leave people guessing:
Data Scientist
Decision Scientist
Insights Strategist
Analytics Partner
Business Intelligence Lead
Quantitative Researcher
Data Storyteller
To the people inside these fields, those titles signal important distinctions. Outside those circles, they may all sound like “does something with computers.”
Which brings me to my simple claim: explaining your job is a data storytelling opportunity.
Because it has the same root challenge:
the work is complex
the context is missing
the terms are unfamiliar
the audience doesn’t know what to listen for
So the solution looks familiar, too:
start where the audience is
provide context
make it concrete
explain why it matters
What I learned at Google: lead with context (not credentials)
At Google, I worked in People Analytics. I quickly realized that leading with my job title (“People Analyst”) led to the same glazed-over look I’d gotten in banking.
I tried starting with context. Instead of saying “I’m a People Analyst,” I’d say something like: “Google is a very data-driven company. So much so that they use data not just for products and marketing—but also for one of their biggest assets: people. I work with data in HR. I help leaders understand things like what makes a great manager, or what influences whether someone stays at or leaves the organization.”
Same job. Totally different entry point. This mattered: people could track with the story because I wasn’t expecting them to already know what “People Analyst” meant. I was building their understanding from familiar ground: Google, data, decisions. That’s the heart of storytelling—making something relatable and understandable.
A LinkedIn post that made me smile (and proves my point)
Recently, I was tagged in a LinkedIn post by a dad in Belgium. He shared a picture of his daughter reading Daphne Draws Data (that I used at the onset of this post) and described a moment that made me smile.
He wrote about how his kids described data after reading the book:
“Data is a beautiful princess!”—his two-year old.
“Data are numbers. And you can use data to help other people.”—his four-year-old.
Then he shared something even more meaningful: the book helped his kids understand what he does for work. Not “computers.” Not “math stuff.” Something closer to the truth: “He makes drawings of data to help people.”
I love this for so many reasons. First, kids are brilliant. Second: that framing is objectively better than most job descriptions I’ve heard from adults. And finally: it’s a reminder that what makes something understandable isn’t the accuracy of the label—it’s the clarity of the explanation. Titles rarely do that, but stories do.
Three ways to explain what you do (without losing people)
If you’ve ever struggled to explain your job to someone outside your world, you’re not alone. You’re not failing. You’re just bumping up against a very normal communication gap.
Here are three tactics that can help.
1) Start with who you help or what you enable. Instead of a title, lead with a “helping” statement.
“I help leaders make better decisions using data.”
“I help teams understand what’s happening and what to do next.”
“I help organizations communicate complex information clearly.”
This gives people an immediate anchor.
2) Explain through an example. People understand examples far more quickly than definitions. Try a single sentence that starts with: “For example…”
“For example, I analyzed what predicts employee turnover so we could test ways to reduce it.”
“For example, I help teams figure out which steps in a process cause the most drop-off.”
“For example, I redesign charts to executives can quickly see what matters.”
3) Use a “because” sentence. This is one of my favorite patterns because it forces meaning.
“I work with data because it helps people make smarter decisions.”
“I analyze customer behavior because it helps teams build better products.”
“I teach data storytelling because insight isn’t useful if nobody understands it.”
Why this matters (beyond small talk)
On the surface, you might think this is about making conversation smoother at parties. That’s true, but it’s bigger than that. When we can’t explain our work, we make it harder for others to value it. This can have the undesirable result of making our impact invisible. We hand people a label and hope it does the heavy lifting. When people don’t understand, they disengage. This isn’t solely a social problem—it’s a professional one, too.
So yes: explaining your job is a data storytelling opportunity. And, like most data storytelling scenarios, it gets easier once you stop trying to be comprehensive and start trying to be clear.
Because the goal isn’t to sound impressive; the goal is to be understood.
Related: On the topic of job titles, if “Data Storyteller” makes your ears perk up—we recently opened a role here at SWD. We’ve had an incredible response and will be closing the application window soon. If you’re interested, please apply by January 23rd.
