The University of Massachusetts Amherst

DACSS Students Hired as Research Analysts at the UMass Donahue Institute

Thursday, July 29, 2021

Ian Dinnie and Kazmeria (Kassie) Breest, master’s students in the Data Analytics and Computational Social Science (DACSS) program at UMass Amherst, are applying the knowledge and skills they are developing in the DACSS program by working as research analysts in Economic and Public Policy Research at the UMass Donahue Institute (UMDI). Ian and Kassie graduated from UMass Amherst with a degree in economics with a minor in history, and a degree in economics with a minor in mathematics, respectively.

At UMDI, the Economic and Public Policy Research (EPPR) group conducts economic impact analysis, socioeconomic research, and population estimates. As research analysts, Ian and Kassie provide support on various UMDI projects that are both quantitative and qualitative in nature.  

Roles at UMDI relative to DACSS

Kassie has worked on projects like the Economic Impacts of Plainridge Park Casino.

“My work was getting into more complex projects and analysis that was less about just crunching the numbers and more about the organizational analytics of it-- like how we want to set up projects and reach out to clients,” Kassie said.

Ian has worked on projects like the recent study of COVID-19 Disparities in Massachusetts across two waves where he wrote R code to estimate age-adjusted death rates by race in Massachusetts.

“A lot of my experience at UMDI has been deeply technical and most of my time is spent around data cleaning and acquiring, manipulating, and analyzing,” Ian said. “Sometimes I contribute to report writing, but most of my skill set revolves around computationally intensive research work, which is what I enjoy doing.” 

While both Ian and Kassie have been able to learn from analysts within EPPR through tutorials and explanations, DACSS has given them formal training in the topics and taught them some new things along the way. 

Interest In and the Discovery of the DACSS Program

Kassie’s interests lie in analyzing and interpreting data. 

“When I started working at UMDI, I helped with any and everything that there was to do” Kassie said. “That’s what got me interested in DACSS. I was exposed to so many different things I could be working on, whether it was mapping or population estimates or economic impact analysis.”

When Kassie attended a poster session hosted by the DACSS program her senior year at UMass, she knew instantly from the types of projects presented that this was the program for her.

Take-Away Skills From Classes

As analysts who are constantly working with survey results and other research data at UMDI, Kassie had attended a poster session put on by the DACSS program her senior year at UMass and instantly became interested. Ian and Kassie have benefited from the detailed knowledge they have gained about research methods in their DACSS classes.

In DACSS 695SR Survey Research Methods, Ian learned more about the overall survey process and how it relates to the data he works with on a regular basis. 

“I work with the end product of survey research methods all the time but I never knew more than the basics. I didn’t know anything about sample weighting, or different types of bias that go into measures,” Ian said. “DACSS survey research methods made me have a more robust and holistic understanding of the data I work with on a day-to-day basis.”

“DACSS survey research methods gave me a really good view of what goes on behind the programs and deliverables that we see in the research field,” Kassie added. “When looking at research for literature reviews, I now have a much better sense of what I should be looking for and have the skills to recreate and adapt their work.”

Learning R as part of the  DACSS curriculum has enabled the research analysts to simplify their work in a fool-proof manner.

“My colleague had a data set broken up into a dozen different files saved on our network drive; it was in total a million observations, 100 different columns, and 12 different files, which doing by hand in Excel isn’t impossible... but it’s super tedious and error-prone,” Ian said. “I wrote an R script that automated that for me and does the work correctly every single time.”

However, it’s not just the programming language, but the programming mindset itself that has helped research analysts with problem-solving. 

“Learning a programming language, like R, teaches you how to think in terms of algorithms and logical sequences,” Ian said. “Besides just the syntax of code, it’s a really important mindset to be able to approach a problem from a high level and work through it in smaller steps.”

DACSS has also offered other classes of interest that have expanded Ian’s and Kassie’s research analysis skills.  

“I took a time series econometric class which was really cool because I can use those skills I learned doing projections in that class on projections for COVID data in the greater Boston hazard report card,” Kassie said. 

Classes of interest

Some of their most anticipated classes in the DACSS program are Text as Data and Data-Driven Storytelling. 

“Text as Data is particularly interesting for me because we learn about machine learning,” Ian said. “I had some project experiences where I think, ‘We need to automate this,’ but I don’t know how yet.” 

The DACSS program has given Ian and Kassie skills to bring back to the workplace. Some of their colleagues have also become interested in the program and started taking courses as well. 

“One of our coworkers is taking DACSS 601 Data Science Fundamentals now!” Kassie mentioned.

See what skills the DACSS program has to offer.