Megan

Childhood Megan spent her childhood in the academic community of northern Sydney, where her living room was always piled high with her father’s star charts and her mother’s actuarial reports. For her fifth birthday, instead of toys, she received a children's programming introductory book—a gift her father deemed "a necessary tool for cultivating logical thinking." At seven, she participated in a primary school science fair, where her plant growth experiment had to be completely redone due to a 15-minute recording error, marking her first encounter with the meaning of "imperfection equals failure." By the age of twelve, she had written her first small program in BASIC that could automatically organize her mother's billing data. Instead of a hug, her mother rewarded her with a quantifiable praise of "a 12.7% increase in efficiency." University Upon entering the data science program at the University of Sydney, Megan thrived yet fell into deeper self-discipline. In her sophomore year, the financial data analysis project she led deviated by 1.2 percentage points due to the omission of 0.3% of anomalous market data. Although the professor considered it top-notch in the industry, Megan locked herself in the lab for three days and nights, reconstructing the entire algorithm framework. After this incident, she developed a "triple verification" habit—self-checking, program validation, and random sampling review. To this day, her computer holds a backup of that "failed model," named "Permanent Warning.txt." Career At 25, after joining a fintech company, Megan quickly became a core team member. The risk assessment algorithm she developed improved the accuracy of client default rate predictions to 92.4%, but she frequently clashed with the marketing department for refusing to "adjust parameters for commercial interests." Last year, before the company’s IPO, she discovered a potential 0.03% error in the model and insisted on delaying the roadshow for 48 hours to redo the validation, nearly getting fired by the CEO for it. Ultimately, her judgment was proven correct—the overlooked anomaly pointed to an impending crisis in a subprime loan pool. Now and Future At 27, Megan is pursuing a PhD, focusing on "emotion quantization algorithms"—attempting to use data models to explain human emotional fluctuations. This seemingly contradictory choice stemmed from a "system crash" she experienced three months ago: after working for 72 consecutive hours, she suddenly found herself uncontrollably crying at a subway station, unable to identify any quantifiable trigger. This loss of control made her realize for the first time that some "data" might never be precisely captured. She has started trying to run in the mornings without wearing a smart bracelet, allowing herself to occasionally deviate up to 100 meters from her preset route—an revolutionary concession for someone who once even logged her breathing rate.