Knowledge Gained, Knowledge Shared
Martin Pollack ’22 shares with other students interested in data-related careers skills he acquired during internships.
Martin Pollack ’22, a math and German major from San Francisco, came to Grinnell with a love of math already rooted in his psyche. Here, he discovered a passion for statistics that soon became a concentration and helped round out his interests and skill sets, which he is now sharing with other students.
“I always really loved math so I always kind of knew I was going to be a math major,” he says. “That helped me learn to work through really hard problems and how to persist through them. But then I kind of was introduced to statistics, and I just really fell in love with how it allows you to make decisions out of uncertain situations. When you just have data, you don’t have all the information. So, the question becomes ‘how can I make something of it?’ And I found that really fascinating.”
Pollack has put his skills to work in a data science internship at Mission Bio, a startup biotech firm in San Francisco; as a machine-learning intern with the Kum and Go corporate offices; and again, as a data science intern at Marsh McLennan in New York this past summer.
While the knowledge he gained at Grinnell helped him land these internships, he found there was still much more to learn when doing the work.
“During an internship you often hear things like ‘Oh, you should know this or be able to do this,’” he says. “So, I had to kind of teach myself some skills while I was doing the internship itself.”
With the realization that advance knowledge of these skills would have been beneficial, Pollack decided to create a series of seminars to help other students interested in similar work get a head start on acquiring this knowledge.
With assistance from the Data Analysis and Social Inquiry Lab (DASIL), Pollack created a series of five workshops that will provide students with some hands-on experience with Python, the most popular data science programming language in the world.
“We want to give students a broad understanding of data science as a discipline,” says Pollack. “And we want to provide an introduction to all the main tools and software that are used and then hopefully get them excited about the field and get them a good head start to keep learning on their own.”
Materials created by DASIL student mentors will comprise the five seminars, which will be offered from 7 to 8:30 p.m. Thursdays, starting the first week after spring break. To date, nearly 140 students have signed up to participate.
The series is free to all students and will cover such topics as Intro to Python, Intro to Machine Learning and AI, Implementation of Machine Learning in Python, Intro to Database and SQL, and some Intro to Big Data using Hadoop and PySpark.