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My number one criterion when looking for an MS program was curriculum – I knew I needed to learn to write better code and get much better at applied statistics and math. But the more I learned about CUNY SPS, the more I appreciated that it is a student-first institution. The faculty and staff are totally dedicated to making sure students succeed.
I wanted a curriculum that was rigorous but practical, which CUNY SPS’s MS in Data Analytics degree has. CUNY SPS is also eminently affordable.
I interacted a ton with other students via in-person and online channels, which were always great experiences. Any tech-focused workplace involves lots of remote collaboration so going through an online learning program and using tools like GitHub to coordinate projects is a great skill to have.
I did a group project on building energy use simulation that used changepoint analysis (which suggests if and where an ordered series of numbers changes), and I’ve come back to it over and over again since it was a statistical technique I didn’t know about but have since applied in several real-world applications.
How to research quantitative and programming problems on my own. There’s no way to learn every statistical method or every programming skill you’ll need for real problems over the course of a degree program. You need to develop the ability to characterize your problem and do the research in order to find the best practical solution. In my work I’m constantly uncovering methods to perform, say, time series modeling or association mining that I didn’t actually cover during my MS in Data Analytics education, but can nonetheless understand and implement.
It was an essential experience for allowing me to actually perform at a high level as a data-focused product manager. It’s not just about perception, I can “walk the walk” and produce results because of the skills I gained.
I fulfill a combined product management and data analyst role, so one thing that is really rewarding is I can switch between more technical problems, like how am I going to understand a customer churn model, to more human problems, like how do I build consensus around a product road map. The technical problems are invariably easier to solve!
I would love to be working at a startup getting a technology product launch from scratch.