Can you describe the degree you are currently pursuing?
I am pursuing a Master of Data Science for Public Policy at the Hertie School in Berlin. The program is a combination of a public policy degree with intense data science skills, exploring how we might combine them for societal good.
What problems do you think data science for public policy should be solving?
In my work as a research assistant, we are looking at how we can use artificial intelligence (AI) and data science to make privacy regulations more transparent for users. This happens at the intersection of policy, data science, and machine learning with the goal of converting legal language into a machine-readable format that can then be more accessible through chatbots or browser extensions. My Master's thesis, on the other hand, aims at testing the limits of remote sensing to detect power infrastructure in developing countries. These tasks, while at first very different, both aim at applying data science tools in environments where society may benefit from its greater efficiency and cost-effectiveness.
What part of your Minerva experience most significantly informed your current perspective on the world and the way you approach studying now?
Academically, I started out with a focus on economics at Minerva but I got lured more and more toward the data science track. The idea that we should use quantitative methods to design policy and think about economics to evaluate programs was something that piqued my curiosity at Minerva. We did not have many courses that were purely theoretical in nature. Most courses were quantitatively driven, especially in my track as an economics and data science major. This is how I think about the world as well. I look at the world and think: What does the data say? How could we try and investigate this with data science?
What are some learnings from your Minerva classes that you find yourself applying to your life or studies now?
Something I learned at Minerva is to be responsible for gaining knowledge and finding my own resources. That was especially the case in my fourth year as I was building my tutorials, which are student-created courses based on their interests and passions. Professors may be able to recommend resources, but probably not in the way that we would like them because tutorials are courses designed by us in the end. These courses challenged me to find my own resources and build my own learning goals. Here at Hertie, I have several courses where professors give us tasks without detailed instructions on how to complete them. It is very similar to having to create my own tutorials again. This is a lot of what we do in life anyway, right? Nobody tells us “here is a guide on how to be an adult”, or “how to find a flat in Berlin.” The method of having students work out their own learning goals is very helpful for them later in life as well.
Can you talk me through your Capstone project? In what ways do you think your Capstone work informs what you are doing now?
For my Capstone project, I looked at the relationship between trade barriers and structural development sectoral change within developing economies. I was interested in whether there was a difference between the tariffs on manufactured goods and those on agricultural goods. I had previously read that there was a difference in how the developed world had applied these tariffs on developing nations, which meant that they were locked into producing agricultural goods because their tariffs were lower, so it was cheaper to export them. Through data, I found confirmation of that difference in tariffs. I then analyzed whether there was a relationship behind this difference—how big the difference was and how much there had been a shift out of agriculture in developing countries in the past. While my degree is in data science and economics, I now work in data science for public policy. However, I think here we also think about where we can get data, how good its quality is, if it is fair, and how we might use it to evaluate a policy or a world event.
How did relationships with your Minerva professors help you to get into this program?
I wrote my Capstone with the support of Professor Hadavand who was also my tutorial professor in the fourth year. Meeting so frequently meant that Professor Hadavand and I developed quite a close relationship. Even after having graduated, we still connect from time to time just to catch up. During my time at Minerva, I was going back and forth about what graduate program I wanted to pursue, and where I would like to pursue it. Professor Hadavand really helped me wrap my head around these questions and decide to join the program at Hertie. He also wrote references for me, along with other Minerva professors. Minerva professors in general help you through your academic career and guide you. When it comes to your Capstone project, they encourage you to shape it in a way that is most useful to apply later on in your career. They ask: What do you want to do afterward? Then they help you turn your Capstone into a portfolio piece that you can actually use later on as well.
Were there any Minerva experiences that inspired you to pursue this graduate program?
First, I actually found my current program and university, Hertie School, while reading a paper for one of the tutorials that was written by Professor Lowe from Hertie, who I had a class with just yesterday. That paper inspired me to pursue my current program at Hertie. It prompted me to research the school and I found out that they have a new Master of Data Science and Public Policy, which I am pursuing now as part of their inaugural cohort.
My academic journey at Minerva inspired me to choose this academic pathway as well. More specifically, the Information Based Decisions class with Professor Diamond and, generally, the Minerva econometrics and quantitative social science courses that followed made me realize that I want to combine these two disciplines and study them further. In one of my tutorials, I wrote a paper using a machine-learning model to do an economics project. I realized I wanted to keep working at the intersection of data science and econometrics. Minerva prepared me superbly well for the trajectory I am on right now.
If you were inspired by Johannes' story and are seeking a college experience that will teach you valuable pragmatic skills that will enable you to change the world, apply to join Minerva today.
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Can you describe the degree you are currently pursuing?
I am pursuing a Master of Data Science for Public Policy at the Hertie School in Berlin. The program is a combination of a public policy degree with intense data science skills, exploring how we might combine them for societal good.
What problems do you think data science for public policy should be solving?
In my work as a research assistant, we are looking at how we can use artificial intelligence (AI) and data science to make privacy regulations more transparent for users. This happens at the intersection of policy, data science, and machine learning with the goal of converting legal language into a machine-readable format that can then be more accessible through chatbots or browser extensions. My Master's thesis, on the other hand, aims at testing the limits of remote sensing to detect power infrastructure in developing countries. These tasks, while at first very different, both aim at applying data science tools in environments where society may benefit from its greater efficiency and cost-effectiveness.
What part of your Minerva experience most significantly informed your current perspective on the world and the way you approach studying now?
Academically, I started out with a focus on economics at Minerva but I got lured more and more toward the data science track. The idea that we should use quantitative methods to design policy and think about economics to evaluate programs was something that piqued my curiosity at Minerva. We did not have many courses that were purely theoretical in nature. Most courses were quantitatively driven, especially in my track as an economics and data science major. This is how I think about the world as well. I look at the world and think: What does the data say? How could we try and investigate this with data science?
What are some learnings from your Minerva classes that you find yourself applying to your life or studies now?
Something I learned at Minerva is to be responsible for gaining knowledge and finding my own resources. That was especially the case in my fourth year as I was building my tutorials, which are student-created courses based on their interests and passions. Professors may be able to recommend resources, but probably not in the way that we would like them because tutorials are courses designed by us in the end. These courses challenged me to find my own resources and build my own learning goals. Here at Hertie, I have several courses where professors give us tasks without detailed instructions on how to complete them. It is very similar to having to create my own tutorials again. This is a lot of what we do in life anyway, right? Nobody tells us “here is a guide on how to be an adult”, or “how to find a flat in Berlin.” The method of having students work out their own learning goals is very helpful for them later in life as well.
Can you talk me through your Capstone project? In what ways do you think your Capstone work informs what you are doing now?
For my Capstone project, I looked at the relationship between trade barriers and structural development sectoral change within developing economies. I was interested in whether there was a difference between the tariffs on manufactured goods and those on agricultural goods. I had previously read that there was a difference in how the developed world had applied these tariffs on developing nations, which meant that they were locked into producing agricultural goods because their tariffs were lower, so it was cheaper to export them. Through data, I found confirmation of that difference in tariffs. I then analyzed whether there was a relationship behind this difference—how big the difference was and how much there had been a shift out of agriculture in developing countries in the past. While my degree is in data science and economics, I now work in data science for public policy. However, I think here we also think about where we can get data, how good its quality is, if it is fair, and how we might use it to evaluate a policy or a world event.
How did relationships with your Minerva professors help you to get into this program?
I wrote my Capstone with the support of Professor Hadavand who was also my tutorial professor in the fourth year. Meeting so frequently meant that Professor Hadavand and I developed quite a close relationship. Even after having graduated, we still connect from time to time just to catch up. During my time at Minerva, I was going back and forth about what graduate program I wanted to pursue, and where I would like to pursue it. Professor Hadavand really helped me wrap my head around these questions and decide to join the program at Hertie. He also wrote references for me, along with other Minerva professors. Minerva professors in general help you through your academic career and guide you. When it comes to your Capstone project, they encourage you to shape it in a way that is most useful to apply later on in your career. They ask: What do you want to do afterward? Then they help you turn your Capstone into a portfolio piece that you can actually use later on as well.
Were there any Minerva experiences that inspired you to pursue this graduate program?
First, I actually found my current program and university, Hertie School, while reading a paper for one of the tutorials that was written by Professor Lowe from Hertie, who I had a class with just yesterday. That paper inspired me to pursue my current program at Hertie. It prompted me to research the school and I found out that they have a new Master of Data Science and Public Policy, which I am pursuing now as part of their inaugural cohort.
My academic journey at Minerva inspired me to choose this academic pathway as well. More specifically, the Information Based Decisions class with Professor Diamond and, generally, the Minerva econometrics and quantitative social science courses that followed made me realize that I want to combine these two disciplines and study them further. In one of my tutorials, I wrote a paper using a machine-learning model to do an economics project. I realized I wanted to keep working at the intersection of data science and econometrics. Minerva prepared me superbly well for the trajectory I am on right now.
If you were inspired by Johannes' story and are seeking a college experience that will teach you valuable pragmatic skills that will enable you to change the world, apply to join Minerva today.