After working as a classroom teacher and school administrator for nearly a decade, Sarah Savage realized she was burned out. While pondering her next career move, Sarah thought back on her career as an educator to see how she could draw upon her years of experience while exploring a new interest.
She had developed a curiosity for data while working for ERB, an education advisory company, where she hosted training sessions with school administrators to teach them how to collect and interpret student data. Sarah believes data is an essential tool for transforming the education experience from being like an assembly line to offering individualized learning.
Offering personalized learning at scale is no easy feat; data offers insights into each student’s learning style, which makes it possible to bucket them into groups and teach them according to their learning style.
After completing the Data Analytics Career Track at Springboard, she landed a role as a content data analyst at edX, an MOOC provider. While MOOCs help to democratize education by providing free or low-cost courses from reputable universities, few learners—roughly 15%—ever complete the courses they signed up for. One of Sarah’s first projects in her new role was to do a textual analysis to understand what stumbling blocks prevent students from completing a program, and to adjust course content where necessary.
I was looking for my next move after working as a teacher when I was recruited to work for a company called ERB, which makes standardized tests for independent private schools. I hosted custom training sessions in data analysis with school leadership teams, parents, and teachers.
I loved diving into the numbers and helping schools understand their data. Even though I wasn’t the person creating the charts or crunching the numbers, I discovered that I had many opinions about it.
Administrators always ask “What's the single most important metric we should look at?” I always say, “Actually, it’s more like three.” You also need to know your students. Data is incredibly useful in helping us pick out trends over time, but you should always investigate other things like the curriculum and the classroom. A low test score that follows a certain pattern can tell us something about the student, but then we always have to go back to the actual human student.
In an ideal world, we'd create an individualized learning plan for every student. That is not realistic for most schools, but what you can do is group students according to the type of learner they are. You certainly can individualize homework assignments.
I did a ton of research into various programs. I looked at bootcamps like General Assembly and Thinkful and I even considered full-time programs like the UC Berkeley extension graduate certificate. Ultimately, I decided that Springboard was the one that best met my needs and my goals.
I liked that the program was asynchronous but I also had support from my weekly mentor calls and career services. The price tag of Springboard is more appealing than other programs. I had spoken to a couple of data professionals to ask them about what I should look for in a bootcamp, and Springboard’s curriculum had the right combination of things.
I was certainly nervous. I do not have a coding background of any kind. I learned research statistics while getting my master’s degree, but it wasn't particularly hardcore in terms of predictive modeling or anything like that. I had been ready to make a change for a while and it took me some time to figure out the path.
My mentor was Andrew Olton [technical services consultant at FreeBalance]. He was great. He's very business-oriented so he would push me to learn about business requirements. For one of our projects, he really challenged me to figure out growth metrics and market share and calculate growth potential based on current market share and market size.
When I gave my final presentation, the evaluator said, “Wow, you are the only student who’s taken growth into account.”
I'm a data analyst on the content team. The content team works with university partners to understand what factors affect whether a student will complete a program successfully. So I’ll analyze metrics like time spent on videos, click through rates, and so on. They were pretty excited that I have experience working with school administrators in a persuasive manner to make recommendations based on the data. They liked my combination of technical skills and soft skills, like public speaking.
I found my job through networking on a site called Lunchclub. It’s a great way to practice your networking skills and talk to people. I received a lot of advice about how to frame my experience by emphasizing my customer-facing skills working with sales teams. I also joined a data-centric Slack group called Locally Optimistic where hiring managers can message you directly. Shortly after I introduced myself in the Slack channel, my now boss sent me a message.
Yes. Networking is an iterative process. You have to be willing to follow all the threads and keep following up with people.
What I would say to a lot of Springboarders, especially people coming from non-technical backgrounds, is don't underestimate yourself. Yes, you might be new at this technical stuff, but the program really does prepare you. If you work hard and you do the assignments, you will have enough technical knowledge to get that first job.
The Springboard program is excellent and well structured, but you also need to do the extra work. It’s up to you to be proactive about your own learning