Marcel Pons Cloquells

I got into data science because data makes visible what isn't obvious otherwise: the patterns in how people behave, the signals buried in noise, the stories behind the numbers that change how decisions get made. I care about getting the details right, and I've always worked the same way: define what's enough to be useful, ship it, watch how it behaves, sharpen it.

I'm drawn to systems thinking: how the pieces of the data lifecycle connect matters as much to me as each individual piece. Owning the full stack across engineering and modeling means a faster path from question to answer, and answers that hold up in production.

I work at Cloud and Big Data scale, across the full data stack. AI is woven into how I work at every layer, and I spend time seriously testing where it raises the ceiling in data work: what it can replace, what it amplifies, and where human judgment still matters more than most people expect.

I care about clean abstractions, reproducible environments, and systems that explain themselves. The right system multiplies everything built on top of it. Getting that foundation right is always worth the time.