How I Got My First Job in Data Science: Advice From a Springboard Graduate

Quincy SmithQuincy Smith | 6 minute read | August 2, 2018
Springboard graduate David Gibson

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David Gibson previously wrote about his experience taking both the Introduction to Data Science course and the Data Science Career Track. Now he’s sharing how he landed his first full-time job as a data scientist, what he would do differently if he had to start over, and why he turned down a job offer.

Can you share a bit about your background, education, and what you’re doing now?

While I graduated [this year] with a marketing degree, I became really interested in data science my sophomore year. The characteristics really appealed to me, especially the problem-solving and math-heavy aspects.

I actually ended up switching majors from film to marketing because it was the closest program my school offered to data science.

Now I work at a mobile-first advertising company. We specialize in marketing for mobile devices such as phones and tablets. We do some desktop marketing, but our niche is definitely mobile.

I work in the data and operations department and we’re the first ones online in the morning because we aggregate all the data from the different clients and put it in our own database so the rest of the teams can kind of monitor their campaigns.

We also do a lot of ad-hoc analysis for specific clients. For example, they may want us to do some predictive analysis or a summary of how the campaign is going.

David GibsonHow does your current role align with both your degree and the data science course you took?

It is surprisingly aligned with my degree. Most kids probably don’t go into the career that they get their degree in, at least not with their first job. It’s really close to my marketing degree, just with different acronyms and the lingo for advertising. And then with Springboard’s course, it definitely aligned as far as the programming end of it because I’ve done a lot of automation for cleaning reports and merging all the client data.

In addition, the course helped a lot with the scripting of R and Python. I haven’t been able to do as much of the more predictive analysis, the machine learning aspect, but that is something that our department is starting to dabble in more as the processes become more automated.

The role I’m in now is the perfect path to building the fundamental skills and becoming a full-fledged data scientist.

What was the job hunt like after finishing college and the Springboard course? How many jobs did you apply to, and was it easier or more difficult than you thought it would be?

It was harder than people say, and I actually started in December, the month before the course started, so I was actively searching throughout the entire program. I started my job in May.

In the end, I probably applied to over 200 jobs as well as sent dozens of cold emails and messages on Linkedin. One of the main issues was that I was living in Florida at the time and they have little to no data science community, which makes networking really difficult. I was almost entirely reliant on online channels of communication.

Out of the 200 jobs that I applied to, I got 10 to 12 interviews and 99 percent of those were through cold messaging on LinkedIn or reaching out to a recruiter or to someone in a data science department and kind of getting my foot in the door.

Can you go more into your process during this time?

My entire process was heavily focused on the willingness to learn and my drive, because I would play the card, “Hey, I’m a marketing student. But I know the importance of business and data science and I’ve taken my time outside the classroom to enroll in these bootcamps and to do all this additional work because I want to learn.”

So I kinda played the role that, “I’m not the Stanford graduate who will make a machine learning model on the first day, but I will continue growing with the role.” My main goal was to demonstrate that I would continue to learn with the company and never be stagnant in the position.

When it came to the outreach I always focused on, “Hey, I would love to learn more about your company and what you’re working on.” Never so much on, “Hey, I wanna learn about open positions.” Instead of saying, “Hey! I wanna get a job with your company!” I was like, “Hey, I wanna learn about what your team does, and what the roles look like.”

So how did you end up getting the job you’re in now?

I just feel like I fit the role really well and the manager kind of saw a little bit of himself in my application. Despite all the cold messaging, the application was through traditional channels and not a message on Linkedin.

It’s pretty much the perfect fit because it’s about 200 employees, half here in San Francisco and half in London, and it isn’t too small or too big. It’s exactly what I was looking for as far as the size and the role and everything.

Do you have any advice for other recent graduates or people just starting their data science job hunt?

I think just the willingness to learn a new technology is extremely important. Focusing on one language, like being an expert in Python, is great, but knowing the fundamentals of Python, R, SQL, etc., will show companies that, “Hey! I have a basic understanding of X, Y, and Z and I’m willing to learn other technologies as well.”

In short, I think trying to be more of a generalist while being willing to grow into roles will serve you better than only having one tool to fall back on.

In addition, during the interview, it’s important to always have something to talk about with the technology. For example, I realized a lot of companies were asking for experience with cloud computing or distributed computing technologies, so I incorporated that into one of my projects and was then able to reference AWS during interviews.

Finally, I suggest talking to as many people at the company as possible—definitely more than just HR and the hiring manager. For example, during one company’s phone screening process, I had a call with someone who had recently left the company and they were very transparent with their thoughts and told me, “Yes, you’d learn a lot, but as far as company growth, I don’t see the company going more into the data analytics side.” And I actually turned down an offer because of that conversation.

If you were going to re-enter the application process, whether it’s out of college or out of a course like Springboard, would you do anything differently?

I probably would start later. I started really early with actual applications when I should have been more focused on networking. If I were to do it over again, I’d focus more on networking. Especially if you’re enrolled in a course where you can’t even work for three-plus months.

In addition, I’d be more focused with my outreach. I probably wouldn’t try to send out as many messages as possible and instead do more research to figure out which companies I actually want to work for and really narrow it down for specific industries.

In the end, I did know what I was looking for and that resulted in a great fit with my current job, but it took a long time to get there, as I had no idea where to look when I started the process.

Quincy Smith

About Quincy Smith

Quincy is a seasoned SEO + digital marketer with experience designing, executing and measuring inbound strategies.