The Long and Short of It
- Attend recruitment sessions. These sessions genuinely focus on helping applicants, literally a cheat sheet.
- Apply good data visualization principles. I may have skimmed a little Edward Tufte—but the key takeaway was clarity and intention.
- Focus on third-order analysis. Not just what the data says, or why, but why it matters. Your dashboard should tell a compelling story.
- Don’t be afraid to network. This isn’t just about “getting your name out there”—it’s about talking to people in the industry you want to be in. What does an actual day look like?
- Learn the language. Be able to speak both technically and in business terms. This came up again and again in conversations. I found this resource helpful in bridging the gap.
- Show grit and apply yourself. Even if you’re not accepted, the Data School provides amazing feedback.
My Journey
I knew I wanted to work as a consultant full-time and made that decision in August of last year, after finishing an internship at a reinsurance company. I didn’t have any formal qualifications, but after exploring different types of coding, I was especially drawn to data analysis. It felt like the technical counterpart to the kind of work I had done as an English PhD—and, incidentally, the only technical skill I’d been exposed to in my formal education.
I started self-studying with a structured schedule: two-week sprints, regular retrospectives, and ongoing interviews with college alumni, academics, and anyone in my network who inspired me. By February, I had locked into a rhythm. That’s when I stumbled across a Data School listing on LinkedIn. It immediately caught my attention—but the application deadline was only three days away.
I decided I would wait for the next round. But curiosity got the better of me, and I went ahead and completed the application in three days. It’s still somewhere on my Tableau Public—and let’s just say, it definitely looks like it was done in three days but I left the experience feeling animated by what I could accomplish with time.
When I reapplied a few months later, I had shaped my entire self-study around the Data School application process. I collaborated with a former Data Schooler in Germany to create a strong dashboard. I spoke with dozens of consultants—not purely to network, but to build a large "dataset" of what a Data Schooler is. I wanted to know whether this was work that was attractive to me.
That ended up being my favorite part of the entire process—even though it wasn’t required or expected.
By the time I got to the second interview, I was nervous (because I cared!), but I knew I had done everything I could to position myself as a strong candidate.
Final Takeaway
If there's one thing I’d share with future applicants, it’s this:
Focus on quality and intention; the choice will be obvious!