As the final application deadlines for our next Data Science Bootcamps in NYC and San Francisco inch closer by the day, we'd like to share the transcribed Q&A from last month's Open House in NYC, during which five Metis alumni, at various stages of their data science careers, discussed Bootcamp experiences, current jobs, and helped Metis staff answer questions from the curious crowd.
Metis Head of Careers Megan Ayraud led the discussion, which featured Kevin Chang, Strategy Consultant and Data Scientist at IBM, John Keating, Data Science Apprentice at Annalect, Allison Chau, Associate Data Scientist at Annalect, Wilson Kung, Data Scientist at Aliya Financial, and John Gilling, Data Science Apprentice at Kaplan Test Prep.
The Metis alumni panel at last month's Data Science Open House
Megan: Hi everyone, and thanks for being here. If you could start off by sharing your name, where you work, and your job title, then just a little background on what you did before coming to Metis, that would be great.
Allison: My name is Allison. I'm currently working at Analect, which is a marketing firm. My title is Data Science Associate. Before Metis, I just graduated in May and then went into the summer cohort. I studied genetics and did some bio-medics research.
John K: Hello, everyone. My name is John. In a previous life, I was an historian. Right now, I'm also at Analect, but I'm an apprentice.
Kevin: Hi, I'm Kevin Chang. I am currently at IBM as a Strategy Consultant and Data Scientist, kind of a multi-encompassing role. My background is actually in electrical engineering. I did consulting for the semiconductor industry for six years.
Wilson: Hi, my name is Wilson Kung. I'm currently at a Fin-Tech company called Aldea Technology. They're out in Connecticut. Prior to Metis, I was working as a consultant, and prior to that, I was in finance for a number of years.
John G: Hi everyone, my name is also John. I'm working right now at Kaplan Test Prep as a Data Science Apprentice. I have a background in mathematics and I spent the last 5 years teaching public school in Boston.
Megan: Thank you, everybody. Tell us about your experience here at Metis...what you liked the most, maybe some of the biggest things you learned, or some of the takeaways that still stay with you today?
Allison: At Metis, I really enjoyed having so many resources everywhere. Also all the people, all the members in my cohort, they came from such diverse backgrounds. Also the instructors, they all seemed to know a lot about everything. It felt like you could ask them anything.
John K: It was very challenging. But I think that if you're here this evening then you, like me, enjoy that type of thing. It was fun.
Kevin: For me, it was primarily the challenge. The instructors are good at putting a concept in front of you and then letting you go figure it out. If you run into a challenge, they're there to help you, but it's your work. You feel accomplished when you understand it, when you get it to actually do what it's supposed to do.
Wilson: My biggest takeaway is the just confidence that I gained from the three months. Before joining Metis, I had fears like, will I be able to get through some of this stuff? I had to ignore that voice and then apply to Metis. I got in. The best thing is just being able to get through all those projects and being able to see that I was able to push through things even though I didn't think I would be able to.
John G: I'd have to mirror what Wilson said. My cohort was made up of people from all different walks of life. We had historians, like John, we had people from education, we had people who worked in business, people who'd been working with data but not necessarily as a data scientist. You learn a whole lot of stuff here. A very broad scope is what this curriculum covers, but you also find your specific passion within that and you find the things that you want to focus on as you go forward as a data scientist.
Megan: What was the day-to-day like for all of you? Was it coming in and having your heads down all day? Were there breakout sessions? Was there time to collaborate? What was your overall experience like?
Allison: Every morning, we did pair programming, which was really cool because, even in college and taking computer science classes, you don't really get a chance to do that much. There were lectures. Then in the afternoon, you had time to work on projects.
John K: This is a very rich space. There are areas on this floor where you can focus intently on your project, but also there are places, like here [gesturing to the space], to hang out. That's a very enriching way to learn. I could work intensely and then chat about it with fellows from my cohort. They would revive me and spur new ideas.
Kevin: First thing in my day was coffee, which is free here. Then we had the pair problem, which we took for a different spin and got competitive with it to see who could write it in the least number of lines possible. After that, it was digging deep. It was running into problems, challenges, and fighting through it all with your cohort. Anyone who got stuck was not afraid to ask for help and bring people over to brainstorm together. It was a lot of collaboration time. I think everyone grew a lot from it.
Wilson: I would spend my time in the classrooms until the class portion ended, generally until early afternoon. Then, depending on my mood, I'd either stay in the room and collaborate with other people, or if I was getting a little distracted by something, I might go to the phone booths here and worth because I tend to be able to focus more that way. This space is great because you've got a lot of different places to work from. The couches are great if you want to just relax and watch some videos for a little bit, take a break.
John G: Again, I'll mirror what these guys said. A typical day is more structured toward the beginning of the day, when you might learn about a specific new thing. Towards the end of the day, you break off and work on your own projects and your own exercises. Also, the semester as a whole kind of follows that same pattern. Towards the beginning of the semester, you're learning a lot more and trying to meet deadlines and doing things. It opens up a lot towards the last four weeks, especially when you're working on your final project. At that point, you get the chance to really explore and design a true data science project, which I thought was really cool.
Megan: Two part question. What's your job search been like? And what was it like working with the Careers Team?
John G: My job search has been pretty short so far. I graduated in December. During Christmas and New Year's, I was not actually looking for a job actively. Then, I came back from vacation and followed up on all of the things that happened at Career Day...all the people I met, all the business cards I collected and traded for. Throughout my apprenticeship so far, I'm still looking for full-time positions as well, but I'm really trying to make sure that I find the right match.
Working with the Careers Team has been great. We have Megan, we have Jen, and they're here for literally anything you could possibly want to talk about, from early offers to what if I never get an offer. They're a really good resource.
Wilson: I graduated in September. I got started interviewing about a month prior to graduation. I approached the Careers Team and they started giving me some contacts to people they knew at the time. They have tons of contacts in all different industries, including New York and on the other side of the country...basically everywhere. I started interviewing and within two or three months, I had three offers. Toward the end, things started getting crazy. I had to start turning down potential interviews because, inevitably, you're going to get a data challenge and those take a lot of time. So in the end, I started having to turn some down. That was my experience. The Careers Team is really great. They really care and they really want to help you out and make sure you get a great job that you love.
Kevin: In my experience, it started a little slow. Of course, it's also what you put into it. I was not putting out applications as fast as I probably should have. Our cohort was also fighting fourth quarter, which is usually a down-turned time for a lot of companies.
I think I'm the only one here that can really speak to the long distance relationship. After the cohort, I was here for a few weeks and then went on vacation overseas. After that, I went back home to Dallas. So I was nowhere near here, but prior to leaving, I had a great video chat with Megan. Jen set down with me, too, and we got aligned on where I was and what I was doing. Even when I was in Dallas, there were a lot of conversations going back and forth on Slack about status, and contacts, and connections through the Metis hiring network. Everything was great. I ended up taking the position at IBM and driving all the way back up here to NYC.
John K: When you're an historian with an intimate knowledge of two dead languages, your career landscape is very different compared to when you are a data scientist, I assure you. It's really nice to be the belle of the ball. I can wholeheartedly endorse the Careers Team here. I have had a lot of mediocre career services through universities and it was nothing like the professionalism and effectiveness of Megan and Jen.
Allison: The job search wasn't a very long process. After I presented my final project at Metis, my employers were actually in the audience and they contacted me about an intern position that could turn full-time. The Careers Team was really great because, from the beginning, I was pretty worried about my prospects of getting a job since I didn't have work experience.
Megan: Thank you, guys. I think we'll bring up the Metis team and open it up to questions.