Miki Seltzer
Featured MIDS Alum

Miki Seltzer

MIDS 2016
Data Scientist
Vivint Smart Home

Miki Seltzer graduated from the School of Information with a Master’s in Information and Data Science in 2016. She currently works at Vivint as a Data Scientist. Prior to the I School, Miki completed a Bachelor of Arts in Applied Mathematics at Yale University.

What is an information challenge that intrigues you?

I believe that one of the biggest challenges with information in the current age is the interpretation of huge amounts of data. As a data scientist, distilling insights from incomprehensible data is key, as well as being able to explain these insights to people who might not be data-savvy.

Why did you choose the I School?

I chose the MIDS program because it offered a chance for me to evolve from an analyst to a data scientist without sacrificing precious years of real-world working experience. I am lucky to work in a place where I was able to immediately apply the concepts I was learning in my MIDS classes to the work I was doing.

What has been your favorite class at the I School?

One of my unexpectedly favorite classes was Field Experiments, because it unveiled to me the mechanics and steps that researchers must take in order to run well-formulated experiments, especially when obtaining large amounts of data may not be feasible. On the other end of the spectrum, I also enjoyed Machine Learning at Scale, which was one of the most helpful classes in using technology and platforms that are widely used outside of an academic setting.

What are you doing now?

I am currently working as a data scientist at Vivint, a home security and home automation company. I was lucky to be able to start the MIDS program about 6 months after starting this job, which is when the volumes of data that we were collecting started to grow quickly. We work with tremendous amounts of IoT (internet of things) data to create products and seamless experiences for our customers across a multitude of smart home devices.

Do you have any advice for aspiring data scientists?

Never stop learning! Data science is continuing to evolve, so continuing to learn about new technologies and methodologies is a must-do to stay relevant. It is also an incredibly broad field, so find the area that you enjoy most and excel in that area. It's better to be exceptional in a smaller number of things than to be mediocre in a larger number of things.

Last updated:

October 11, 2018