All in a day’s work at an AI powerhouse

Data Science and Economics student Gao Yuchen, who’s graduating as part of the inaugural College of Humanities and Sciences (CHS) cohort, aspires to become a machine learning (ML) engineer in the e-commerce industry - where she hopes to design and deploy ML models to optimise customer experiences and enhance products.

Her internship at ByteDance was not merely a means towards this end. Indeed, this “purpose-driven” experience proved to be the bridge which led her to secure full-time employment in the same team, even before her graduation. 

As a data engineer intern at ByteDance, Yuchen was responsible for building and maintaining data products that support business development teams. In doing so, she had the opportunity to work closely with cross-functional stakeholders to ensure that her solutions aligned with business needs.

She says, “I wanted to gain real-world experience at the intersection of data engineering and business operations within a fast-paced e-commerce environment. This was how I could apply my technical skills to solve practical problems that directly impact business outcomes.”

She adds, “I am especially proud of leading the development of the Business Development (BD) Leader Workbench, a data analytics platform that significantly enhances visibility and decision-making for the BD team.” 

Yuchen’s work focused on designing data models to track the full lead lifecycle, building a comprehensive key performance metrics system to monitor conversion, timeliness and efficiency, and creating dashboards to track operational efficiency at both team and individual levels.

She also implemented analytical tools such as funnel analysis and performance benchmarking, along with features for anomaly detection. By ensuring data reliability, responsiveness, and usability, the platform improved BD business efficiency and contributed to higher success rates in merchant onboarding.

During her internship, Yuchen got to observe at close range how the business operates, how teams collaborate and how decisions are made.  

She says, “Technical correctness alone isn’t enough. Communicating with business stakeholders and understanding core business goals and its operational context are just as critical. The true value comes from aligning technical work and actionable data solutions with business and user needs.”

She adds, “My internship experience affirmed my interest in building scaleable data systems that directly support business decision-making. I'm excited to deepen my expertise in data infrastructure, pipeline optimisation and stakeholder collaboration.”