For over 10 years, Maura Fields worked long hours as a production coordinator for TV commercials in LA and New York. Every day was different, and travel opportunities were extensive. In a nutshell, her role was to be a project manager for commercial shoots–running the production office, coordinating schedules, and filling out paperwork.
But in mid-2020, when production shut down for four months at the onset of the pandemic, Maura had time to ponder her next career move. Like many professionals, she had stuck with a job she took straight out of college, but this time, she wanted to make a more deliberate choice.
She had first considered a career change in 2018 and even had a few meetings with career coaches, but she couldn’t figure out what she wanted to do. While working as a production coordinator, she had especially enjoyed managing budgets using Excel spreadsheets, so she decided to explore that thread. That’s when she landed on data analytics.
After graduating from Springboard's Data Analytics Career Track, Maura landed a role as a data analyst at Northeastern University, where she collects, analyzes and repurposes data to support university rankings determinations.
I was basically a project manager for different commercial projects that I would get hired to do as a freelancer. Part of my job involved using Excel to track budgets and other aspects of a project. It wasn’t data analysis, but I always felt some sort of satisfaction when I worked with an Excel spreadsheet.
It's a very fast-paced environment. The projects are very short-term, so you hit the ground running. It has taken me to different places around the world and I’ve made some great friends. The TV commercial industry in New York in LA is small, so you get to know a lot of people. The disadvantage is the hours are long and there aren’t a lot of boundaries regarding work/life balance. As I was getting older I started wondering if it was still worth it to work from 5:00 AM to 1:00 AM the next day.
I work at Northeastern University within the office of university decision support. That office is responsible for reporting data to outside publications like Princeton Review and the U.S. News and World Report to maintain their rankings. We also deal with adh hoc data requests from within the university. For example, if a department has a specific question or is applying for a grant.
Yeah. It's been less than a month and I already have a few projects under my belt. I use Tableau and Tableau Prep everyday, which the Springboard program definitely prepared me for. Of course, there’s still a learning curve. I’ve never worked in higher ed before, and their data is specific to them. They also use some older software programs which you wouldn’t necessarily learn about in any current data analytics course.
The main skill I learned in production is time management. Now that I’m working on data analytics projects, I understand how long it takes to do something and manage my time well. Attention to detail is another one. I don’t necessarily build new queries all the time in my role–I mostly update existing information from a previous academic year–but making sure that I’m giving the correct information.
There were two things that stood out to me. First, it was one of the few bootcamps that had a data analytics focus. A lot of boot camps offered courses in data science. The one-on-one mentorship was a huge draw for me as a career shifter. Having an industry expert I could rely on to teach me not only the technical aspects but learn about the business itself was really important. I also liked that the program was self-paced because I studied while working full-time.
My mentor had worked for EA Sports for a long time and was one of the first analysts at Lyft when the company was founded. He’s very technically advanced and has been in the industry for a while. He was so patient with me. I asked a lot of questions that were probably very basic, because I didn’t have experience with data. We actually met in-person once. He was traveling to Russia and had a layover in New York, so we met up for coffee. After I graduated, we kept in touch on LinkedIn and he was willing to put me in contact with people within his network while I was searching for a job.
My first capstone project was inspired by the Black Lives Matter marches after George Floyd was killed. I decided to look at the number of police shootings by race because there was a lot of discussion around police brutality. One of the interesting things about data is that you can take an emotional issue and use data to dig deeper. I used data on police shootings in the United States from 2015-2020 and compared it to U.S. Census data to estimate the probability of being shot by a police officer based on race. I found that black males were twice as likely to be shot by police than white males.
Teach yourself how to use different tools and ask questions to your colleagues or supervisors. Practice is important, too. The more I use Tableau, the more I understand it. Also, the more interviews and technical assessments I completed during my job search, the more I learned.
Quite a lot of time passed between when I initially graduated from Springboard and when I landed a job, but because I have lifetime access to the course materials, it was like having a library I could rely on to reference things I’d learned. I will also say that the curriculum and tools I learned at Springboard are the ones I use in my day-to-day role as a data analyst, especially with regards to Excel, Tableau, and SQL. I think the Springboard curriculum was spot-on.