Skip to main content
Academics

An Uncommon Thread

New Ag Data Science Certificate binds grad student’s studies, research, and career prospects

To say Shelly Hunt is busy would be an understatement. She is a graduate student in biological and agricultural engineering, a team member on a major NC State research project supporting the sweetpotato industry, and a year-round intern at SAS, one of the world’s top data analytics companies.  

Hunt is also enrolled in the Ag Data Sciences Certificate program, which she chose to pursue instead of a minor in statistics. So far, the 12-credit program is proving to be the perfect complement to her studies, her field research, and her career goals.

We interviewed Hunt to better understand how this unique certificate is simultaneously solidifying her success as a student, providing an avenue to practice what she is learning, and brightening her prospects for a future career as a data analyst in the agriculture industry.

At what point in your scholarly journey did you learn about the Ag Data Sciences Certificate program?

In my junior year of undergrad at NC State, I wanted to get involved in research and think about where I wanted my future to lead. Given my math and engineering experience, I wanted to go into analytics. It wasn’t until I started taking classes with Dr. Natalie Nelson, though, that I knew what I wanted to do. It was my first real dive into data analytics in agriculture, and I haven’t looked back since. 

After joining the bio and ag engineering department as a graduate student, I began talking about my options for minors with my research advisor, Dr. Dani Jones. At the time, I was choosing between a minor in operational research and a minor in statistics. That was when Dani told me about the certificate program, which is similar to getting a minor. At that point, I was choosing between a minor and a certificate.  

Why did you enroll in the Ag Data Sciences Certificate program? 

At the end of the day, the certificate was better for me. When my master’s degree gets printed, it will say ‘biological engineering.’ When you look at that, it can mean a lot of things. It can mean eco engineering, bioprocessing engineering, or something else. This certificate conveys what I specialize in. All classes have direct relationships to stats, data science, research methods, data collection, and a lot more. When you think of Bioengineering, Data science isn’t what you initially think of. This certificate shows future employers what I’ve specialized in. It makes it easy to convey to others where my expertise is. Also, I wanted to add to my diploma collection!

You are involved in a major ag data analytics research program related to sweet potatoes. Tell us more about your work on this project.

Yes, I started with the Sweetpotato Analytics for Produce Provenance and Scanning (Sweet-APPS) team, which supports one of the GRIP4PSI programs on the N.C. Plant Sciences Initiative. I joined in May 2020, working as an undergrad through summer and fall. Then I remained in the program when moving to graduate school. In short, I capture data, tidy it up, and improve our models.

We study what governs the shapes of sweet potatoes. We look at the distribution of different shapes in a given yield, and we use machine-learning algorithms to predict shapes of tubers based on biological, cultural, and management practices. 

We capture information in the form of images and render them in 3-D software. Using algorithms, we can record the physical characteristics of sweet potatoes – like length and curvature, then we can classify and tie them to production data, like slope, soil texture, where that potato came from, and other things. That’s one main part of my research with this team. Another part of my work is stakeholder engagement, mostly with North Carolina producers. I talk with them, trying to understand their needs for data exploration and model building. These conversations help drive the final product we’re trying to deliver: a tool farmers can use to predict the shape of their spuds. They also help drive new research questions which we can maybe answer through the data or through new research. 

I have really loved working for this project. I’m now a weirdo that goes straight to the produce section at the grocery store who looks at the shape of sweet potatoes and tries to figure out where they came from!

How has the Ag Data Sciences Certificate program helped advance your work on this Sweet-APPS project?

It has 100% helped. I can think of two classes – one on advanced analytics in agriculture, food, and life science data with Dr. Dani Jones and the other on ag data analytics modeling with Dr. Nelson – that have been especially helpful with my work. In both classes, we are assigned hands-on projects where we’re encouraged to use real-life data from our research. These classes let me use the data from my work with the Sweet-APPS team, which has directly impacted my success on the research team. This has made me more efficient with writing code and shown me how to use exciting tools and technologies. SAS, a major data analytics company, has a software title called Visual Analytics. It’s a phenomenal tool where you can create interactive dashboards that can be used in data science. I have used that software to create a dashboard for one of our industry partners we’re collecting data from. I have shown them what to do and what can be done. I wouldn’t have been able to do this without my advanced analytics class with Dr. Jones. This is a mandatory class, so it helps others, too.

You are also an intern at SAS. How does the certificate program complement your internship work? 

The certificate program gives me the technical prowess to succeed at a huge software and analytics company like SAS. Because of the data science training I’m receiving in school, I’m able to successfully engage with SAS data engineers, analysts, and even clients to produce meaningful results. As a graduate intern at SAS, I get the opportunity to work with real-world ag production data. I collect, wrangle, tidy, visualize, and analyze this data and can present findings to my SAS colleagues and clients. Working in the AgTech division, I see that there is a huge need in the agricultural field for people who have ag expertise, plus know how to correctly handle and manage all sorts of data, both structured and unstructured.

What is your ideal job in the agriculture industry?

I would love to stay in ag data analytics and be an analyst for a major ag company – either that or work for a large company with an ag division, one that specializes in ag analytics, like SAS. That would be my dream goal. I’d also really like to continue doing outreach to actual producers. That’s one part of my research I love, being able to talk with them. I want a job where I can assess customer needs and create the data driven tools to support them and their operations. 

Would you recommend the Ag Data Sciences Certificate program to others?  If so, who would you recommend this program to, and why?

Yes, there are a lot of super interesting classes you could take, and the classes I’ve taken so far have been outstanding. I would take them again if I could. The program can be a great fit for students with a background in data science or agriculture. There are two tracks to customize the certificate. If you’re a student with a background in data science and you want to learn more about agriculture, you can do that. Or if you come from more of an agriculture background and want to build your data science skills, you can do that too. If you have a background in both areas like me, it’s even better. You can take classes to hone your skills further!