Ying Zheng is Building an Enduring Data Science Career

Developing a Data Science Passion

Ying Zheng (’22, ’24) is a driven data scientist who began working for RTX Corporation nearly four years ago during her master’s program at Embry-Riddle Aeronautical University.

She started at Embry-Riddle's Daytona Beach, Florida, campus in 2019, in the Aerospace Engineering program. However, her aptitude for using math and human performance to solve challenging problems led her to the Computational Mathematics and Human Factors Psychology programs.

“My second year at Embry-Riddle, I switched my major to a double major in Computational Mathematics and Human Factors ... because I wanted to continue learning advanced math,” she said.

After taking several math classes, including Dr. Mihhail Berezovski’s Research Project in Industrial Math course, Ying knew that this field was her strong suit. She decided to major solely in Computational Mathematics to sharpen her math and analysis skills.

“In the [Research Project] class, I collaborated with the Nevada National Security Site on a new pooling method for convolutional neural networks,” she said. “I found myself really enjoying applying math concepts to building and analyzing algorithms in machine learning (ML).”

In her fourth year, Ying transitioned into the accelerated Data Science master’s program, which enabled her to engage in graduate-level data science applications early on. She began to see what being a data scientist would look like and undertook several real-world projects to gain experience before graduating.

“I decided to continue at Embry-Riddle because it allowed me to work on my graduate degree while I was still doing my undergraduate degree,” Ying said. “The master’s program gave me hands‑on experience with modern tools and applied ML.”

Staying Agile in Early Career

Ying interned at RTX as a software engineer while completing her master’s program, transitioning into the organization’s Rotational Leadership Development Program (LDP) after graduating. After gaining experience in asset management and program management, she advanced to a data scientist position.

“I rotated through three different digital-focused roles, which gave me a chance to try out different areas while building my leadership skills,” she said.

Ying enjoyed exploring different areas of data science and learning how the field is evolving, especially regarding artificial intelligence (AI).

“I’m seeing that the increased demand for AI and data‑driven decision making has pushed companies to evaluate their data quality, governance and infrastructure,” she said. “We can see organizations improving data accessibility and consistency, because without this, AI initiatives or data-driven decision making won’t produce trustworthy results.”

Directing her efforts toward gaining practical data science knowledge during her undergraduate and graduate programs helped Ying get started, and staying driven and dynamic throughout her early career has helped her step into new and exciting roles. She is evolving with the industry, staying on top of new trends and skills.

“I’ve noticed that the best data scientists are those who can also adapt to their industry and understand business strategy,” she said. “What really makes someone stand out is the ability to combine those skills with industry knowledge and use data in a way that directly supports strategic objectives and drives innovation.”

Connection and Leadership in Data Science

Ying’s operations graduate assistantship with Embry-Riddle's Housing and Residence Life taught her important lessons that she would later apply directly to her career.

“I managed front desk operations and oversaw a team of around 10 student staff members, [so I was] the first point of contact for any escalating student or parent concerns,” she said. “I learned how to stay calm under pressure, listen carefully, de‑escalate situations and guide people through the issue while setting clear expectations and representing our policies.”

Ying's position also involved overseeing several university-wide events. She has often reflected on those experiences while preparing for new responsibilities, environments and unforeseen conflicts in new roles.

“I was responsible for coordinating the logistics behind big events like move‑in, Preview Day and other key events ... which required planning, quick problem solving and keeping things on track even when unexpected issues came up,” she said. “Together, these experiences taught me a lot about conflict resolution, stakeholder management and how I want to show up as a leader.”

Alongside building industry-aligned skills, Ying cites networking as the catalyst for securing professional opportunities. She completed three internships and an assistantship while attending Embry-Riddle, earning them through meaningful connections she established and maintained. Networking also helped her stand out and find new opportunities in and after her rotational program at RTX.

“One of the biggest lessons I’ve learned over the last few years is just how important networking really is,” she said. “Staying connected with people across the organization ended up making a difference. It was through those relationships that I was able to land my current role post-LDP.” 

A Promising Future in Data Science

With several years of management, leadership and data science expertise under her belt, Ying looks toward the next several years with clear goals for advancement and resilience in her field.

“I want to be a technical program manager on an AI- or ML-focused program and, from there, aspire to be in a senior leadership role overseeing enterprise-scale AI or ML strategy.”

Ying is prepared to continue growing in the data science field, ready to take on new challenges and identify new opportunities, backed by her Embry-Riddle education and diverse set of experiences.