Helena Lecluyse

As data platforms, like Microsoft Fabric grow more powerful, the need for human centered understanding becomes increasingly important. Yet when you walk into most data teams, you’ll find computer scientists, engineers, and statisticians – but rarely a psychologist, linguist, or sociologist. For years, the field has signaled that only STEM profiles belong here, causing bright human sciences graduates to filter themselves out before they even try. I am one of those people who didn’t get the memo. With a Master in Psychology, experience in mobile eye tracking research, behavioral experiments, neural network simulations, and statistical analysis in Python and R, I discovered that human sciences training is unexpectedly strong preparation for working on the Microsoft Data & AI Platform. Neural networks are inspired by the brain; language graduates have a head start on LLMs; social science graduates bring years of quantitative analysis and research design. Human sciences graduates work with complex datasets, design privacy aware studies, understand cognitive bias, and translate human behavior into structured hypotheses. These are exactly the skills that separate a Fabric dashboard that informs from one that misleads, an AI feature that gets adopted from one that gets ignored, and a stakeholder conversation that uncovers the real question from one that delivers the wrong report on time. By translating technical complexity for stakeholders, supporting responsible AI, and aligning data work with real world human impact, human sciences graduates offer a strategic advantage. This session shows why data teams may be leaving talent on the table. Technical skills build the system. Human sciences skills make it useful.