{"id":90777,"date":"2026-05-22T12:01:28","date_gmt":"2026-05-22T16:01:28","guid":{"rendered":"https:\/\/www.bu.edu\/cas\/?p=90777"},"modified":"2026-05-28T16:44:00","modified_gmt":"2026-05-28T20:44:00","slug":"alumni-spotlight-xihao-cao","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/cas\/alumni-spotlight-xihao-cao\/","title":{"rendered":"From Classroom Projects to Walmart Forecasting Systems"},"content":{"rendered":"

Alumni Spotlight: Xihao Cao<\/h2>\n

\"\"When Xihao Cao<\/strong> began exploring graduate programs in statistics and data science, he knew he wanted more than a purely theoretical education. <\/span><\/p>\n

With a strong quantitative foundation established through his undergraduate studies in mathematics at the University of Washington, Cao was seeking opportunities to apply those skills to real-world problems.<\/span><\/p>\n

That search ultimately led him to Boston University\u2019s <\/span>Master of Science in Statistical Practice (MSSP)<\/span><\/a> program.<\/span><\/p>\n

Originally from Inner Mongolia, China, Cao says his growing interest in applied mathematics and analytics motivated him to switch to statistics for his master’s degree. <\/span>As data science continued to expand across industries, he became increasingly interested in using data-driven insights to solve practical problems.<\/span><\/p>\n

\u201cI had a growing interest in focusing more on the application side,\u201d Cao said. \u201cUsing data to solve real-world problems and support better decision-making.\u201d<\/span><\/p>\n

Choosing MSSP<\/h3>\n

For Cao, one of the defining strengths of the MSSP program was its balance between rigorous statistical training and hands-on experience. In particular, he was drawn to the program\u2019s emphasis on consulting and practicum work, which allows students to <\/span>collaborate on projects with real clients before graduating.<\/span><\/p>\n

\"MSSP<\/span><\/h3>\n

Through <\/span>MSSP Consulting Services<\/span><\/a>, students work with members of the Boston University community on project planning, data analysis, visualization, and presentation development. The program\u2019s <\/span>practicum component<\/span><\/a> further expands on that experience through consulting projects with Boston-area organizations, including companies, nonprofits, and public-sector partners.<\/span><\/p>\n

\u201cThat kind of hands-on experience is incredibly valuable,\u201d Cao said. \u201cIt helps students transition from an academic environment to an industry setting more smoothly.\u201d<\/span><\/p>\n

Coursework also played a major role in shaping Cao\u2019s professional development. He cites MA 678: <\/span>Applied Statistical Modeling<\/span><\/i> and MA 679: <\/span>Applied Statistical Machine Learning<\/span><\/i> as particularly impactful courses during his time at BU, helping him build a strong technical foundation in applied statistics and machine learning methods.<\/span><\/p>\n

At the same time, the program\u2019s collaborative, project-based structure helped him develop skills beyond technical analysis alone.<\/span><\/p>\n

\u201cI completed two semester-long projects that helped me strengthen not only my analytical skills, but also the soft skills that are essential in real-world data science work,\u201d Cao said. \u201cThings like communicating with teammates and stakeholders and telling a clear story with data.\u201d<\/span><\/p>\n

That emphasis on communication and practical application continues to influence his work today.<\/span><\/p>\n

From BU to Senior Data Scientist<\/h3>\n

Cao now works as a Senior Data Scientist supporting Walmart\u2019s Finance and Merchandise Operations teams, where he designs and develops deep learning-based forecasting systems used across more than 70 merchandise departments and 10 channels within the company.<\/span><\/p>\n

These forecasting systems help guide merchandising plans and sales outlook decisions, combining machine learning, statistics, and business analysis to support operational planning.<\/span><\/p>\n

\u201cMy day-to-day work involves a mix of coding, time series modeling, visualization, forecast validation, and business-facing analysis,\u201d Cao said.<\/span><\/p>\n

Landing the role was no small feat. After applying in early 2024, Cao completed three rounds of technical interviews and one behavioral interview as part of Walmart\u2019s hiring process.<\/span><\/p>\n

\u201cFrom what I remember, only five candidates, including me, made it to the final stage out of a pool of around 200 applicants,\u201d he said.<\/span><\/p>\n

Throughout both the job search and his time in the program, Cao says faculty mentorship played an especially important role in his success. He credits MSSP professors with helping him navigate the transition from graduate student to industry professional.<\/span><\/p>\n

\"They<\/p>\n

Advice for Current Students<\/h3>\n

Looking back, Cao describes his experience at Boston University in three words: practical, supportive, and collaborative.<\/span><\/p>\n

His advice for current students \u2014 especially those hoping to pursue careers in data science \u2014 is to focus less on buzzwords and more on meaningful experience.<\/span><\/p>\n

\u201cIn many cases, recruiters care more about the value you have actually delivered than about how many technical buzzwords appear on your resume,\u201d Cao said. \u201cFocus on building practical experience, communicating your work clearly, and showing how your skills can solve real problems.\u201d<\/span><\/p>\n

And when asked about the best advice he received during his time at BU, his answer was simple:<\/span><\/p>\n

\u201cStart today, not tomorrow.\u201d<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

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