Brandon became a software engineer by attending a coding bootcamp, so when he wanted to shift his career to data science, there was no question he would turn to another bootcamp. He wanted to keep his part-time job and was living in a remote area, so he decided to enroll in Springboard’s flexible online data science bootcamp to learn at his own pace. Brandon tells us how Springboard prepared him for the job search, his salary increase, and how his background in software development helps him in his new job as a Data Scientist at Red Ventures!
What were you up to before Springboard? What led you to study data science?
My undergraduate degree was in Economics and I did not have any programming experience in school. I started out working as an analyst at a consulting firm, but as time passed, I often worked with software developers who were doing really deep technical analysis. They were using software as a tool and I wanted to learn more.
I'm actually a two-time bootcamp graduate. To transition from an analytical role to a full-time programming role, I attended a full-time, in-person bootcamp called Codeup in 2014, where I learned the LAMP stack. I got to work as a Web Developer and I’ve written in a few other languages since then. But data science seemed to be that sweet spot between thinking about a problem in a truly deep analytical sense and having the tools to actually act upon those thoughts. I wanted to solve problems using software and machine learning as a tool.
Since you had already learned to code at a bootcamp, did you consider teaching yourself Python and data science?
I did. I definitely used some self-guided online resources like Data Camp, but in my learning experiences, I’ve really valued having a dedicated mentor, which I had in my previous bootcamp experience and which Springboard offered. The mentorship was really the big selling point for me.
I was looking for a data science bootcamp to help me make that transition. I had done some self-study, but ultimately, I'm a big believer in setting aside a few months and really dedicating it to learning a new skill. I knew the value of setting aside the time and really immersing yourself in a topic.
Why specifically did you choose Springboard? Did you consider any other data science bootcamps, like in-person bootcamps or other online schools?
I had considered some in-person bootcamps, but at the time I lived in a very rural area. Making a four-hour trip to New York or another major metro area wasn’t an option. Whereas at Springboard, it doesn’t matter where you learn from, as long as you have an internet connection and put the work in. I didn’t consider any other online programs – Springboard was already on my radar.
Springboard had the four factors that were the most important for me: the ability to learn remotely, the ability to have a flexible schedule so I could still work part-time, dedicated mentors, and Career Services. They did a really good job providing me a structured way to apply for jobs all over the country and ultimately helped me find something that piqued my interest.
What was the application and interview process like when you applied for Springboard’s Data Science Career Track?
There was a coding and statistics entry exam which took one or two hours. They provided some resources to prepare – exercises in Python and some statistics questions. I wasn't super comfortable with Python at the time, so I had to brush up on syntax. It had also been six or seven years since I had been in a statistics class, so I had to find some resources for that as well. I spent one weekend studying.
Once you started studying with Springboard, what was the learning experience like?
It was a mixture of external resources they had curated, along with custom teaching. Throughout the week I could set my own pace, and decide which exercises to complete. At the end of the week, there was a 30-minute call with a mentor, where I had the opportunity to ask explicit questions about things like career experiences or specifics about machine learning. The questions varied as I went through the course.
Springboard did a very good job listing out how much time to expect a particular task to take. I could plan my week in advance and say, "Here are three things I'm going to finish this week. It's going to take me 20 hours, and I need to be ready by Saturday for my 10am call with my mentor."
It was pretty much a rinse and repeat cycle every week. I would come home after work and work on those things through the evening, maybe four or five hours a night. And then on Saturday, I would work through any problems with my mentor – anything I was stuck on or confused about or just wanted to dig deeper into.
How did you balance your part-time job with studying with Springboard?
I was working part-time on some software development contract work while completing the course.
I tried to stay pretty regimented. Between 9am to 5pm, I worked. After 5pm, I did Springboard. In fact, I would even move to different locations and have different computers so that the worlds did not collide.
Were you able to interact with other Springboard students and work together on projects?
Yes, in a couple of ways. There are online forums where you can ask questions of your fellow students about the curriculum and ask for input from people who might be further along in the course. I also made deliberate attempts to travel to some nearby metro areas, like Washington DC, New York, and Philadelphia for some long weekends, to meet up with some of my fellow students in person and attend some networking events. Part of Springboard’s curriculum actually encourages students to go to data science meetups and make sure that we’re not just learning the curriculum, but actually talking to people.
What did career services at Springboard involve? What kind of advice did they give you for job hunting?
Springboard gave us checkpoints throughout the course. I went through a series of explicit exercises and conversations during the curriculum to help narrow down the types of roles I was interested in, the cities I wanted to work in, and the industries that interested me. Before I sent out a single job application, I had a shortlist of 20 companies to start looking at.
On top of that, they gave us opportunities to practice presentation skills and interviewing. Springboard covered the whole life cycle of the job search, not just, "How do I push my resume and get myself in the door?"
How long did it take you to finish the Springboard program and then how long did it take you to find a job?
I finished Springboard in four months. Springboard recommends taking six months, but I intentionally wanted to push myself to finish it as early as possible. I looked for a job for about six weeks. I had an offer within a week or two of completing the course, but ultimately decided that it wasn't in a location I wanted. It was very affirming to get an early offer, so I felt confident in being picky and taking my time with it.
Congratulations on your new job! How did you actually find that job at Red Ventures?
Thanks! I was contacted by a recruiter at Red Ventures. They contacted me regarding an engineering position, unrelated to data science. I told them that I appreciated the interest, but was looking for a position where I could further build my skills in data science. I shared some of my data science projects from the course that really showcased some of the skills I had developed. They took that very seriously and I had the opportunity to interview for the data science position rather than the engineering position. I got the role and moved to Charlotte, North Carolina, where their offices are located.
What does Red Ventures do and what are you working on there?
Red Ventures is a marketing firm, and we help our clients acquire new customers through various marketing channels: social, organic SEO, etc.
My role as a Data Scientist is to support our products in paid search. When we're running paid ads, we have machine learning systems that help decide when to place an ad, to whom, and what price you're willing to pay for a given ad.
What was the learning curve like when you first started there? Are you using the same technologies you learned at Springboard or have you had to learn new tools?
I have had to learn entirely different tools, which, coming from programming jobs, was totally expected. But the underlying data science techniques are still the same. For example, logistic regression in R is conceptually equivalent to logistic regression in Python. We're even using Scala for some tools. So ultimately, the language and tools are merely delivery mechanisms, the underlying techniques are what matters.
Are you on a team of data scientists or are you working alongside people doing different functions?
We are one team of many at Red Ventures. The team I am on is a mixed group. We have four engineers, two data scientists, two product analysts, and a product manager. It’s a multidisciplinary team, to say the least. And I think that's one of the added benefits of having worked in different roles – I have a better sense of how my co-workers are approaching a particular problem.
How else has your background in software engineering been useful on the job?
The opportunities I've had at Red Ventures have been great because it has been a good mix of both data science demands and engineering demands. The data science techniques are helpful, but without thinking about how an application can build and grow and evolve over time, the data science techniques only take you so far. One of the benefits of working in an interdisciplinary team is that we use those different perspectives when we’re going to build something, and it helps build better products.
Can you give me some specific examples of when your programming background has been useful?
Sure. One recent bit of work involved taking applications and models that we've been running on local servers and migrating them to the cloud – AWS (Amazon Web Services). My programming experience helped me to navigate the process of migrating the applications to AWS. There were specific considerations we needed to make in terms of runtime, model monitoring, and breaking a monolithic application into smaller components.
Having gone through years of building applications, I felt a lot more confident working through those considerations.
You've worked as a Software Developer and now you've worked as a Data Scientist. What are the main differences between working in those two fields? Do you prefer data science now that you're in that field?
For me, the biggest difference in the role as a data scientist is that I have more autonomy to help decide what should come next on our roadmap.
In some of my software development jobs I had very little input into the features I was building. But as a data scientist, I actually get to be part of the conversation where our team identifies and prioritizes features we think are the most valuable.
The fact that I can have that conversation and really drive the direction of the application and how we're working as a team is something I really value.
What kind of role has Springboard played in your success in becoming a data scientist? Could you have got to where you are today by self-teaching?
I think it would have taken me much longer. Is there an abundance of material out there? Absolutely. Would I have been able to curate it for myself or been able to seek out mentors or career support? Yes, absolutely. But it would have taken me months, if not years, longer.
Yes. It was a very nice transition in that regard. I can attest to the results there.
I think it's very market dependent. I lived in a part of the country with a lower than average wage for Software Developers. So part of it was me being willing to move and make that transition.
Have you stayed in touch with other Springboard students? Have you heard if they have found jobs as well?
I got to meet some of my classmates in person for the first time about a month ago. Springboard had a two-day, mini-conference in San Francisco, and I decided to make the trip out to hear some of the speakers and hear some student success stories. That was a really cool event – to go from never seeing any of these people to getting to talk in person and hear how they've succeeded.
The few I've been in touch with who completed the program have either found new roles or taken the skills and applied them to their existing roles. I have yet to speak to someone who hasn't been pleased with their outcomes.
What advice do you have for other people thinking about making a career shift through an online data science bootcamp?
The best advice I can give anyone considering a remote bootcamp would be to set a schedule and stick to it. I would not have been able to complete this course if I hadn’t set a schedule. For people working remotely, being on a regimented schedule is the most important part. If you're in a classroom, you have someone really kind of pushing you. If you're on your own, you have to put that pressure on yourself.