Innovation in Action: A Summer INTERNSHIP at JGM

I recently finished a summer-long internship at JGM Innovation, working with the JGM team to find new insights into links between health and educational disparities in Peru. I initially saw this role as an opportunity to build my skills while contributing to a mission-driven organization, and I’m happy to say I did that and more while working here. What started as a chance to apply classroom knowledge in a practical setting became an experience that challenged me to think critically, push past my comfort zone, and develop both technical and professional skills that I know I will carry into future roles.

As JGM is a small team, this internship offered me the opportunity to adapt to the current needs of the organization. The small size turned out to be a huge advantage, because instead of being siloed into one repetitive task, I was trusted to take on many different roles over my 3 month stint. That flexibility gave me a front-row seat to how a lean, mission-driven organization operates and the importance of each team member’s contribution to moving a project forward.

At first, my focus was on building out a visual map display in JavaScript that could be used to highlight differences in education, health, and other key metrics across the provinces of Peru. To implement this, I worked with JGM’s technical lead, Ruben, to find a way to represent this visually, with the JavaScript library Leaflet. I built out a choropleth map that shades Peru’s provinces differently based on a certain metric such as test scores or obesity rate. This allows us to highlight where educational investment or health outcomes may be lagging in Peru. As this was my first time using geospatial tools, I had to learn how to find and handle shapefiles, clean inconsistent data formats, and ensure the map was rendered in a way that was both visually appealing and interpretable for a broad audience.

About halfway into my internship with JGM, I switched focus to work on data analysis, using AI and the Google suite of tools to turn data into concrete insights. At Ruben’s suggestion, I used Google bigQuery at first, and later Google Colab to clean Peruvian health data and analyze the thousands of rows of individual health information. Using these tools, I was able to produce detailed obesity rate estimates for Peruvian children, and further segment that data by region, age, and gender to get further insight into where this specific health issue is greatest in Peru. Analysis using a pivot table showed that while Male children had a higher obesity rate at age 12, by age 17 Females had the higher rate. Also, the data showed that obesity was a greater issue for both genders from ages 12-14 than it was later in their development. These weren’t just abstract numbers; they revealed patterns that could shape real policy decisions. If young adolescents are at higher risk, then interventions in schools during those years could make a meaningful difference. Knowing my work could positively impact the lives of many children in Peru was incredibly motivating throughout this internship.

Learning how to analyze data at a massive scale was an unexpected takeaway that I have from this internship, as I had initially never done any data analysis. Despite not being exposed to this type of project previously, the JGM team and my fellow interns helped me succeed by giving collaborative, constructive feedback in our weekly demo meetings. This helped me understand when I was pursuing dead end data too far, and learn about the technical strain of different tools.

I also discovered how important communication is in technical work. It’s not enough to just produce a table or a graph; you have to be able to easily explain what it means to people who may not have the same technical background. Every week, I presented my progress in our weekly meeting, which pushed me to translate statistical results into plain language, and to continue iterating on whatever project I was working on.

I’m confident that in the future my experience working with large datasets in this internship will allow me to confidently approach data analysis problems, building on the fundamental understanding of data analysis tools and methods that I gained in this internship. Equally, I know that the soft skills I picked up in my time at JGM will prove extremely useful in my future career. For anyone considering an internship at JGM, my biggest advice is to come in with an open mind. Don’t expect your role to stay static. Instead, expect to pivot, learn new tools quickly, and take ownership of projects that might seem daunting, as that uncertainty is where I grew the most this summer.

Thomas Cordingley