Microbiology and MBA grad JK started to learn about big data and machine learning in his job, but wanted to learn more about data science in a structured environment. He enrolled in Springboard’s Machine Learning Career Track to learn about ML and AI online. JK tells us how he balanced his full-time job with the Springboard bootcamp (hint: he didn’t sleep much), and how networking at conferences helped him land his new job as a Data Engineer at KPMG!
What is your educational and career background?
I didn't come from a computer science (CS) background. My undergrad was in microbiology, immunology and molecular genetics. I then completed an MBA with a concentration in Accounting and Finance, working at the Australian Chamber of Commerce in Korea. And that's where I got a taste of some CS database work. My most recent job involved data engineering so it was almost through necessity that I had to learn more about big data, artificial intelligence (AI) and machine learning (ML).
Why did you choose Springboard to help you learn these new skills? Did you consider trying to teach yourself?
Before considering Springboard, I did try learning some things on my own. I used Dataquest to learn some basic Python, and skills in data science, engineering, and analytics. However, I felt that I needed more structure and guidance to stay on track. For self-guided learning, you need to have a lot of self-discipline to keep to a regimented plan. In a bootcamp, you tend to have someone checking in on your progress weekly. Aside from its glowing reviews on sites like Course Report, that's what drew me to Springboard. Their job guarantee was also attractive to me. Essentially, if you fully complete their curriculum, they guarantee you a job. But I'd say that it's pretty hard not to get job offers once you’re done with the course.
Did you only consider online coding programs, or did you look at in-person courses too?
I considered both. I was also looking into more formal education such as masters degrees. But location was a big determining factor for me. I was located in New Jersey, and if I had wanted to enroll in an in-person program, my only options were in New York City. I just wouldn't have been able to make that commute every day, so online courses were very attractive to me. I could complete the Springboard program from the comfort of my home. I did want to do an in-person coding bootcamp; it just wasn't a practical option for me.
How did you finance the Springboard tuition?
I was originally looking at their Data Science Career Track, which was around $7,500 if you pay up front. For the AI and Machine Learning Career Track, I was in one of the first cohorts, and was offered a discount to take the program. This was significantly cheaper at around $4,500. Fortunately, I had that money available to me and was able to pay the tuition up front. I also had the option to pay in monthly installments. For some of the programs Springboard has introduced an income share agreement model where you don't pay tuition until you've secured a job.
What was the Springboard application and interview process like?
I originally applied for their Data Science Career Track and there wasn't an interview – it was purely assessment-based. I had to complete 10 multiple choice questions covering basic statistics, then do two coding challenges. I was pretty proficient in Python at the time, but if I needed additional help, sites like LeetCode or HackerRank had very similar exercises. I then decided to switch over to the AI and Machine Learning Career Track, so I had to take the multiple choice test for that course, in addition to a slightly more difficult coding challenge.
How much Python did you need to know for the machine learning bootcamp?
They're not going to ask you to do anything too challenging. I have a friend who's also trying to transition into a career in data science, and he isn't as proficient as I am. He’s still new to Python. There are preparatory mini-courses that you can take with Springboard to prepare you for the entry assessment and go on to do the Data Science Career Track. If you're entirely new to it and don't know basic data structures and algorithms, then you're going to have a bit of an issue. If you know the fundamentals, you'll be okay.
What was the Springboard learning experience like?
I liked the Springboard learning platform and how easy it was to use. They have KPI milestones to remind you where you ought to be in the program at any given point to keep you on track. They also have recurring prompts checking in on whether you've received a job offer, or asking if you'd like to schedule a call. I liked this approach.
As for the material itself, the course is essentially a curated list of materials that you probably could source online if you were to go and look for it. That said, the curated all-in-one-place curriculum is what I liked about the course. Springboard partnered with other providers such as DataCamp and Lynda to offer supplementary hands-on exercises. Topics covered included Python, Pandas, TensorFlow, Spark, AWS, data structures, ML algorithms, APIs, neural networks, natural language processing, and more. We also worked towards completing a capstone project with the help of a mentor.
Springboard should continue to keep its course content as up-to-date as possible. Things change so quickly – what you learn might not even be applicable at the end of the program. For example, TensorFlow just came out with version 2.0, but during the Springboard program we were working on a previous version. That said, it's part of the game in this industry.
What was your favorite project or assignment while at Springboard?
I liked anything which involved data wrangling, with Pandas or Spark, for example. I know the track was supposed to be machine learning engineering, but in order to do any sort of machine learning, you need to first clean the data. People in the industry or in academia are probably spending a large portion of their time doing this. For data to be good enough to use for running models, that data has to be cleaned thoroughly.
How often did you interact with your instructors and mentors?
The 30-minute 1:1 call with my mentor happened once a week. At the beginning of the program I'd often have coding-specific questions to ask my mentor. And because the AI and ML field is ever evolving, I'd always be thinking about opportunities to broaden my knowledge and would regularly ask about that. Towards the end of the program I’d share my job interview experiences with my mentor and ask for their feedback.
Outside of that 1:1 call, if I had any questions, or if I was having trouble with the code or need more resources on a specific topic, mentors were always available via email or Skype. They're great people. You get to know what they're doing too. Mentorship goes both ways. I totally see myself reaching out to my mentors again in the future.
Was there much opportunity to interact with other students?
Because it's an online program and we couldn't meet in person, Springboard opened up a piazza, which is an online forum where students can answer each other's questions and discuss topics. There were also official offline Springboard local meet-ups in some of the bigger cities where current students, alumni, and sometimes student advisors, could meet one another.
What kind of schedule did you have when you were going through the program?
I was working at my job full-time but also working through the Springboard track full-time. I’m in Texas now, but before that I was in New Jersey working for a company in Korea. One of the biggest reasons I wanted to switch careers was that I was working Korean hours, which in New Jersey translates to working from 8pm to 5am. I was working all night and sleeping during the day. And then I gave some of that sleep time to working through the Springboard program.
To be frank: I didn't have much time to sleep, or to see friends or family. Knowing it would be short-term, I chose to prioritize and focus on the program. I felt that once I switched jobs, everything else would fall into place. And it has worked out that way for me. I have now reverted to a normal 9-to-5 schedule.
How did Springboard prepare you for job hunting?
One of the most impactful aspects of Springboard is that they make a career coach available to you. In reality, securing a job is not all about the hard technical skills; the soft skills are a large part of what gets you through the interview process. The initial career coaching calls motivated me to attend local events and network. They really pushed me to get out and attend conferences, where I'd be networking with HR managers and with other data scientists and ML engineers – and that really boosted the success rate in my job hunt. For example, I went to conferences like PyCon (the Python conference), where I would literally hand people my resume and they would later reach out to me with leads. Springboard educated us in phrasing correspondence (what to say and what not to say) and essentially: how to sell yourself and your brand to potential employers. I found that to be immensely helpful for my job search.
What was the typical job interview process like?
The interview process normally began with a call from someone from HR who would walk me through the job description, to check off competencies, and to make sure that I was an amicable human being. The second phase was a more in-depth, more technical interview with a hiring manager to showcase my past projects and responsibilities in my current role. At that stage, I would usually have to complete an online assessment or have a technical interview where my Python and SQL skills are gauged. After that, I'd be invited to attend an in-person interview. For these, sometimes they'd stack up to six separate interviews back-to-back. Occasionally, I’d have to work on whiteboard; sometimes I would be asked questions about a case study. If at this point this they liked me, I would receive an offer. From time to time, there would be a final interview with someone at perhaps VP-level to ensure that I was aligned with the company goals and its vision. All in all – depending on the company need – the interview process took between a week and a month-and-a-half.
How did you find the job you're about to start?
Networking. By the end of the Springboard program I had received four job offers and they all came about through networking. Just by having a conversation with someone, you can be referred for opportunities that aren't even listed online yet. And that's what happened for me. I had sent out an endless number of resumes and had seen no success doing it that way.
Can you tell me about your new role and what you'll be doing day-to-day?
I'll be working at KPMG, which is one of the “big four” in accounting. But they also offer all sorts of other professional services. One big vertical is on the tech side. They have a group called Lighthouse which is their Center of Excellence for Data and Analytics. They provide IT consulting to firms who may not have the resources to be able to architect or deploy certain solutions in-house. We visit companies who might not have a dedicated tech team (perhaps in the finance, insurance or medical fields), evaluate their way of doing things, and work towards architecting a big data solution for them, according to their business needs. This might mean going to a regional supermarket chain that is using a very siloed data solution and wants to change this. We leverage our knowledge and subject matter expertise to improve their solution.
Do you use the same technologies that you learned at Springboard?
Springboard gives you the fundamentals. Everything after that is a slight variation of something else you have previously seen, so I don't anticipate having to learn anything vastly different.
In this world, you do have to keep abreast of industry developments and constantly be refreshing your knowledge. While I have a firm grasp of a lot of big data techniques, there are always going to be new technologies.
How will you leverage your previous experience in your new job?
In my experience, there are typically those who focus solely on the tech and there are those who are focused on the business side of things. Then there's usually some kind of go-between function. The tech-business go-between translates whatever the business side needs to the technical side so that they can implement it. And I’m used to fulfilling that function. I think what KPMG liked about me is my ability to understand what a layperson might say to me and translate that into how it could be brought to life on the technology side. Before my current job, I also worked at the chamber of commerce in a client-facing capacity. A lot of the time, the client would have a vague requirement for us. They would have an idea and it would be up to us to flesh it out into something more actionable. KPMG liked the fact that I could take an idea, ask the right questions, and figure it out. They want people who can take incomplete questions and assumptions and create something that has substance and impact.
Do you think you could have got to where you are now through self-teaching alone?
Hypothetically, if I had continued with my approach to self-teaching, I might eventually have been able to land a job like this. But it's a question of when. I had been trying to progress as self-taught for a while and my success rate was zero. It was only once I went through Springboard's program that my response rate became much higher than zero. But I really don't know if I could have landed the job through self-teaching alone.
What advice do you have for other people who are making a career shift by going through an intensive program like you did?
I would say: trust the process. I was very skeptical when I first set out on the program. You just have to suspend your disbelief.
Imogen is a writer and content producer who loves writing about technology and education. Her background is in journalism, writing for newspapers and news websites. She grew up in England, Dubai and New Zealand, and now lives in Brooklyn, NY.
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