{"id":54691,"date":"2025-11-04T12:06:52","date_gmt":"2025-11-04T17:06:52","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ams\/?post_type=news&p=54691"},"modified":"2025-11-04T12:14:42","modified_gmt":"2025-11-04T17:14:42","slug":"decoding-the-human-side-of-data","status":"publish","type":"news","link":"https:\/\/engineering.jhu.edu\/ams\/news\/decoding-the-human-side-of-data\/","title":{"rendered":"Decoding the human side of data\u00a0"},"content":{"rendered":"

As Chloe Dearman ’25 completes her master\u2019s degree in <\/span>Data Science<\/span><\/a> at the <\/span>Whiting School of Engineering<\/span><\/a>, she is not just culminating an academic journey that has afforded her opportunities to learn firsthand about the power of data in decision-making, but she is also embracing her calling to leverage data science for impactful change. Whether it\u2019s enhancing patient care or guiding audiences to their next favorite TV show, she\u2019s asking herself the same question: how can data improve lives?<\/span>\u00a0<\/span><\/p>\n

This past summer, Dearman worked behind the scenes on the HBO Max product analytics team at Warner Bros. Discovery, where she witnessed the transformative power of data in real time. <\/span>\u00a0<\/span><\/p>\n

\u201cWe analyzed viewer behaviors\u2014what shows were clicked, how far users scrolled, and where<\/span> they lost interest,\u201d she explains.<\/span> \u201cI wasn\u2019t just observing data move\u2014I was contributing to how the platform connected with its audience.\u201d<\/span>\u00a0<\/span><\/i>\u00a0<\/span><\/p>\n

As part of a team responsible for end-to-end reporting across HBO Max and Discovery+ apps, Dearman helped track and interpret user activity from the moment someone opened the app until they closed it. When a new feature launched that enabled users hover over a title to preview a show, her team analyzed how often people used it, how engagement varied among audiences, and whether it changed viewing patterns. Their insights informed stakeholders about which features to refine or expand. <\/span>\u00a0<\/span><\/p>\n

Through this process, Dearman says she strengthened her understanding of how analytics drive business strategy. \u00a0\u201cIt felt surreal to work on something so many people interact with daily,\u201d she says. \u201cSeeing how analytics guide real-world choices made me realize this is exactly what I want to do in my career.\u201d<\/span>\u00a0<\/span><\/p>\n

Her drive to make an impact continued during her time at Johns Hopkins School of Medicine\u2019s <\/span>Center for Data Science in Emergency Medicine<\/span><\/a> where she\u2019s helping develop machine learning models that predict whether patients will need critical care, using real-time hospital data. <\/span>\u00a0<\/span><\/p>\n

\u201cI\u2019d never conducted research before coming to Hopkins,\u201d<\/span> Dearman says. <\/span>\u201cNow our team is submitting manuscripts for publication. It\u2019s been incredibly meaningful\u2014and rewarding.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span>Getting to this point hasn\u2019t been without its challenges, though. After spending two years in consulting, the technical coursework of a master\u2019s program felt daunting. <\/span>
\n<\/span>\u00a0<\/span><\/p>\n

\u201cI had to rebuild my coding confidence,\u201d she says.<\/span> \u201cBut the classes at Hopkins pushed me in the best way.\u201d<\/span>\u00a0<\/span><\/p>\n

A deep learning course with <\/span>Vishal M. Patel<\/span><\/a>, associate professor of electrical and computer engineering, proved pivotal. <\/span>\u201cWe didn\u2019t just learn the tools,\u201d<\/span> she says.<\/span> \u201cWe learned how to think like researchers\u2014how to keep learning beyond the classroom.\u201d<\/span>
\n<\/span><\/p>\n

Her upcoming capstone project brings those lessons together. Using natural language processing\u2014a form of artificial intelligence that helps computers understand human language\u2014Dearman built a custom web scraper to analyze publicly available customer reviews for the clothing brand Uniqlo. The independent project explores how different models interpret sentiment and how demographic data might reveal deeper insights into consumer behavior.<\/span>\u00a0<\/span><\/p>\n

Building on those insights, Dearman applied state-of-the-art natural language processing (NLP) techniques, including the BER<\/span>T<\/span>\u2014an advanced Google model that interprets language context\u2014<\/span>to refine for approach to sentiment analysis. In doing so, she developed a stronger grasp of how data preprocessing, model selection, and interpretation can reveal patterns in customer behaviors that inform both business and consumer decision-making.<\/span>\u00a0<\/span><\/p>\n

<\/span>Whether she\u2019s parsing streaming data or analyzing hospital records, the common thread is clear: <\/span>\u201cIt\u2019s about people,\u201d<\/span> she says.<\/span> \u201cIt\u2019s about helping them find the right product, the right show, the right treatment, at the right time.\u201d<\/span>
\n<\/span><\/p>\n

She\u2019s planning a career as a data scientist and credits the master\u2019s program\u2019s flexibility and mentorship for her growth and sense of direction. <\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Her advice to prospective students? <\/span>\u201cDo your research.\u00a0 Hopkins offers you so many opportunities to explore and the freedom to build your own path\u2014and the tools to make it happen.\u201d<\/span>\u00a0<\/span><\/p>\n","protected":false},"template":"","class_list":["post-54691","news","type-news","status-publish","hentry","news_categories-data-science","news_categories-research","news_categories-student-experience"],"acf":[],"yoast_head":"\nDecoding the human side of data\u00a0 | Department of Applied Mathematics and Statistics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/ams\/news\/decoding-the-human-side-of-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Decoding the human side of data\u00a0 | Department of Applied 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