“How do I do more of this?” That’s what I wondered as I walked out of a meeting with a prospective client. Before Springboard, I was a banker, and I’d just presented a new visualization of financial data that I’d created myself. The client was impressed – not every banker makes that effort. But I wasn’t satisfied. I had a lot more data, and a lot more ideas about what I could do with it. If I only knew how.
As I looked around, I realized I needed to learn Data Science to do what I wanted. At first, I tried picking up tools like R on my own. I joined online courses and watched lectures. But without someone there to hold me accountable, I found myself leaving many of them unfinished. I posted to message boards like Stack Overflow, but I didn’t always get the answers I needed. Sometimes, my posts got downvoted. More often, I didn’t even know the right questions to ask.
I started doing online tutorials, but that wasn’t enough. Then, I came across Springboard. I liked the fact that they had somebody to help you along the way.
Things changed when I started working with my Springboard mentor, Brandon. In emails and weekly calls, I finally had a chance to talk to an expert who could help me on parts I didn’t understand. For example, when I found myself struggling with a difficult data set, Brandon took me step by step through it, explaining how the data was structured and how to write functions for it. It was the kind of challenge that I would have given up on when I was on my own. But with Brandon’s help, it became something I understood, and an achievement I could be proud of.
Having someone who cared about my success ensured that I made progress every week. If I didn’t finish what I said I would by our weekly call, I felt like I was letting Brandon down. It pushed me to work harder. And Brandon helped – he was generous with his time and advice, and he had my back.
When I started Springboard, I had an idea to use company stock data to predict future earnings. I’d tried doing it earlier, but I didn’t know how to make predictions for many stocks at once. My goal was to make predictions for over 100,000 stocks that I had data on.
By the end of the program, I had the pieces together to build a working model. As my capstone project, I used what I had learned about data munging and machine learning to make predictions for all the stocks in my dataset across an entire year. So far, the model has been right 75% of the time!
My experience with Springboard helped me make the leap from an investment banker to a Data Scientist. Today, I work at SESAC, which represents the performing rights of 30,000 singers, songwriters, composers and musicians. I’ve helped set up their data infrastructure and warehousing, and I work with our extensive datasets to help make the business better.
Right now, I’m working with a dataset with 5 million rows that has information on royalties for musical artists. There are thousands of ways to slice and dice it and pull out meaningful information. Because of Springboard, I know how to consider different approaches, and I have the experience to use techniques like k-means clustering to do it.
Springboard was a key step in my career – I’m not sure I’d be where I am today without it. It has some of the best mentors available, with a great curriculum that will really get you beyond just an entry level understanding of Data Science.