Yuzhu Zhang 张语竹
I grew up in China and studied German. I was very interested in a structured way to interpret the world and then later change the world — which is how I ended up in Berlin studying sociology, political science and public policy.
During my studies I became drawn to quantitative research — the idea that data could make arguments rigorous, that you could let numbers speak rather than just assert. That's what eventually pulled me into the private sector, into data-intensive domains where those questions had real stakes.
Outside work, I spend my time reading, hiking, and bouldering.
How I got here
I've worked across three industries — advertising, logistics, and pricing — in roles that each gave me a different lens on data. What connects them is that I've always been more interested in what the numbers mean for a decision than in the numbers themselves.
Where I studied
- Hertie School of Governance, Berlin Master of Public Policy · focused on evidence-based policy, governance, and quantitative methods
- Humboldt University Berlin Social Science (Political Science & Sociology) · exchange and further studies
- Beijing Foreign Studies University German Studies (BA) · German language, literature, and European studies
A few things I actually believe
Most data problems are not really data problems. They're decision problems — someone isn't sure what to do, and they're hoping data will resolve the uncertainty. Sometimes it does. Often, the real work is clarifying the question before anyone looks at a dashboard.
I came into product management from the analyst side, which means I have a strong instinct for what data can and cannot tell you. I'm skeptical of metrics that feel clean but measure the wrong thing, and I'd rather have an honest uncertainty than a confident number that nobody trusts.
On AI: I think the most useful thing you can do right now is treat AI tools as a real colleague rather than a search engine. Not because the outputs are always good — they're not — but because the process of working with AI changes how you think about your own work. The teams I've seen benefit most are the ones who engage critically, not the ones who delegate blindly.
I also think documentation is underrated as a strategic asset. Most teams treat it as overhead. The ones that treat it as a product — with users, feedback loops, and actual maintenance — tend to work faster and make better decisions.