Bingbing Huang was wrapping up his third year at a startup when he applied to the professional master’s program in computer science (MCS) at Rice University.
“While studying for my B.S. in computer science at the University of Washington, I enrolled in several data science courses and they really piqued my interest. I wanted to go deeper into data science, but I was already doing research in another lab and exploring industry jobs; I just didn’t have the time to pursue it further,” said Huang.
“Rice’s MCS program offered the chance to specialize in data science and machine learning while improving my software engineering tool kit and increasing my career opportunities.”
His work at a healthcare technology startup focused on software engineering solutions for the company’s data science team, but it also introduced Huang to the importance of clear communication with a wide variety of audiences — including job applicants. He offers three bits of advice for candidates as they prepare for technical interviews.
“First, be sure to articulate your ideas clearly and obviously. Use English to explain your ideas, not math and not terms that only specific users know,” he said.
“Second, don’t waste time; come to the point. I know you want to give as many details as possible, but we have only a limited amount of time. Interviewers have to summarize the candidates in data points for a scorecard that indicates whether or not we are inclined to hire them. When someone talks a lot without coming to the point, interviewers can’t easily summarize that candidate for the scorecard. Candidates who make quick and clear points fare better.
“Finally, talk slowly so you can synchronize and resonate with your interviewer. Watch their facial expressions and stop as needed, to clarify or ask them a question. What you need to do in an interview is leave an impression. Make yourself the candidate that is memorable.”
Huang’s communication skills were well-developed when he began the MCS program at Rice, but he took advantage of several campus resources to raise the bar. One of the workshops offered in the George R. Brown School of Engineering is Intensive Oral Communications Coaching, which includes individual coaching, group work, and software programs to address international graduate students’ most challenging verbal communications. Katerina Belik, who completed her Ph.D. at Kuban State University in Russia, is one of the IOCC lecturers.
“Dr. Belik taught us about reading the facial expressions of people in our conversations or meetings,” said Huang. “For example, one head nod indicates they are probably following you. But if they just keep nodding without actually making eye contact, they are not understanding at all.
“That is the time to slow down. Talking slowly gives other people time to interject their ideas or ask for clarification. If they are still showing their ‘confusion face’ to you, then stop and proactively ask if they understand a specific part or if they would like you to explain it further or differently.”
When Huang is being interviewed, he prepares by researching the engineers he will meet. Looking at their projects helps him shape the kinds of examples he might use.
“If their work is not aligned with mine, I will try to learn more about their software language and what programs they work on. Then I direct my answers to the areas they are most likely to understand. For example, are they writing in an object-oriented or functional programming language? I don’t have to know the specific language because I am familiar with the fundamental concepts of different programming languages,” said Huang.
Like all employees at small startups, Huang wore a lot of different hats. In addition to his software engineering responsibilities and interviewing candidates, he worked directly with customers and corresponded with colleagues at partner organizations and third-party software providers. The company hired in-house physicians, and Huang also worked with them to help integrate their knowledge with services the startup was providing.
Huang said, “No one can know and do everything, so you will have to share information — and depend on others to use that information— to achieve success for your project. Collaboration is so important. That means articulating ideas quickly, efficiently, and with good quality.”
Although it sounds counter-intuitive, speaking slowly is actually conducive to making points quickly and efficiently. Drawing diagrams is another aid to explaining an idea or solution, while using technical terms and acronyms is a hindrance.
“Engineers in general tend to love jargon,” said Huang. “Everyone has their own favorite specialty or niche. With so many different specialties, it is unlikely to encounter an audience with a lot of members who are experts in the same area as the speaker. Eliminating jargon goes a long way to getting your point across.”
Another area in which Huang excels is reiterating and restating his points, when appropriate, in a conversation or meeting. Rather than saying the same words again, he rephrases them to reinforce understanding. In a similar way, he has learned to ask questions in different ways.
“Being able to learn and adapt is important when talking with consumers and partners from various backgrounds. I had to be able to request their feedback and also ask if they understood, without offending them,” he said.
“It may be different in a large established company but in our startup, the engineers often interfaced directly with customers. We could ask them questions about their requirements, about improvements we wanted to make, or how a defect was manifesting itself. To get the most out of these kinds of conversations, engineers really need strong communication skills - something engineers have not been trained for in the past.”
Huang said that lack of communication training is what makes it easier for the engineers who do improve their skills in that area to stand out in the field. He had the opportunity to improve his own communication skill with every conversation: interviews, team meetings, customer conversations, and discussions about technical requirements.
He said, “Talking with partner or third-party engineers about our platform was completely different than talking with internal colleagues because we had to protect our intellectual property (IP). We had to find ways of explaining our idea or issue without talking too much about our core technologies. In most cases, we would develop algorithms specifically for demos in order to prevent exposure of our technology to external collaborators. Explain without leaking IP information—that is very important!”
At Rice, Huang said his interests continue to expand but he remains passionate about the combination of statistics, machine learning, and software engineering that make up data science. In addition to giving him space to dive more deeply into data science, Rice has also impacted his professional skills in several significant ways.
“I’ve learned to be more self-aware: to objectively evaluate myself and determine if my own words and actions match my internal standards, as well as how others view me through those words and actions,” he said.
“Rice has led me into more critical thinking: to think about both personal and professional problems from different perspectives and to address them based on the whole picture and various collected data instead of solely on my own individual thoughts.
“The classes and activities presented to me have also taught me to prioritize more wisely when resources are limited: begin by sorting out tasks based on their priorities because, as a human being, you only have a limited amount of time and energy. If you bite off more than you can chew, you may end up getting very little accomplished.”
Obviously, Huang has no difficulty articulating those ideas.
This article was originally published for the ACTIVATE Engineering Communication program.