You’ve all heard about judging coding bootcamps and data science bootcamps based on their outcomes (aka does a bootcamp get students jobs), but we rarely get the perspectives of both the bootcamps and the employers at the same time. So we were really excited to have our guests, Megan Ayraud of Metis and Brennan Biddle of Capital One Labs, join us for a video interview.
Meet Your Panel:
Megan is the head of careers at Metis, a Data Science bootcamp in New York, San Francisco and now in Chicago. Megan helped develop the 12-week Careers Curriculum, which is concurrent with the bootcamp curriculum at Metis, and provides a lot of post-graduation support for Metis students.
Brennan is a Data Science and Data Engineering Recruiter at Capital One Labs in New York, which is an employer partner of Metis.
It can be really difficult to sort through job placement rates and stories about bootcamp grads who've gotten jobs after graduating. In this live Q&A, Megan and Brennan answered all of our questions about how Metis prepares future data scientists for their first jobs, and how an employer like Brennan can hire effectively from a coding bootcamp like Metis.
Megan and Brennan, can you first tell us a little bit about your roles. Megan, what does it mean to be the Head of Careers at Metis?
Megan: As the Head of Careers at Metis, I work with all of our students and graduates on helping them through the job search within the current data science market. As you mentioned, I've built a curriculum that goes alongside our data science curriculum, and it's all about developing them in their career and getting them prepared for the job search post-Metis.
There are workshops built into the 12-week bootcamp, one-on-one meetings, mock interviewing, and we bring speakers in who are data scientists in the community to help shine a light on what data science is like in their companies. I organize a career day at the end of every bootcamp cohort and we invite employers to meet our students and network. I also work with all of our students individually, along with my career advisors. Shout out to Metis’s amazing career advisors, who help find our grads amazing jobs.
Likewise, Brennan, what does it mean to be a Data Science & Data Engineering Recruiter right now?
Brennan: The fact is that the term data science means a million different things to a million different people. Even internally within Capital One, we're a big machine. Different groups in different corners of our business define data scientists differently. The hardest part is finding the right candidates that match up with specific needs of each individual group within our organization and finding where those technical strengths lie.
Brennan, are there baseline requirements needed to be a data scientist at Capital One? Do candidates need a certain type of degree?
Brennan: Really good question. I can't speak to everywhere, but here at Capital One, we want our data scientists to essentially wear a research and development hat coming into the door. Our Data Science organization is the most random, diverse, crazy, eccentric group of people you'll ever work with. Just sitting in my little pod alone, we have a Neuroscience Ph.D., a Math Ph.D., and a former high school math teacher. There's not one specific type of a person or background, either personal or professional, that we're looking for. I usually tell candidates the weirder background you come from, usually the more successful you'll be as a data scientist here at Capital One.
That actually aligns really well with bootcamps because everyone who graduates from a bootcamp has a past life or career.
Megan, how do you coach students on incorporating their past lives with their future lives as data scientists in just 12 weeks?
That imposter syndrome is a common problem and we work with our students a lot, not only in groups and workshops, but also a lot of one-on-one mock interviewing. When we’re working on the technical interview, we actually bring data scientists in and have them actually go through a real live mock interview as students can expect in the real world.
That helps build a lot of confidence in soft skills, and how to present your background and tie in your past life to your new life as a data scientist. It's amazing to see that transformation. A lot of people say, "I was a math teacher in my former life, how could I possibly tie that into data science?" As career advisors, we see that connection so clearly, but it's our job to help them develop that narrative, practice it, build confidence, and then be able to tell that story to employers.
Brennan, have you hired Metis graduates?
Brennan: We have hired a few!
What types of roles are Metis grads going into at Capital One Labs? Does Capital One have a Junior Scientist role?
Brennan: Yeah, we do. Even for a “junior” data scientist, we're looking for a really strong foundational data science background. This for us is someone that is really good a Python, has at least a little bit of exposure to working in a Hadoop framework, and someone that is interested in functional languages.
We do have junior level roles (although they don't pay like junior level roles). We anticipate hiring someone that we can grow, mold and develop. And we find that places like Metis do a really good job of building that foundation that we can build upon.
How did you meet the students that you've hired from Metis? At a career day or did you guest-lecture at Metis?
Brennan: The answer is both. Metis has had a few cohorts and we've been working with them throughout. Our team goes to the Metis classroom, introduces ourselves to the cohorts, tells them what we do, and learn about the projects they're working on. The last cohort came in for a career day to see our office space and interview and they asked a lot of questions of different data scientists on different teams. Metis has a career night that we attend every single cohort as well. At this point, we have a pretty good relationship with them at different stages in their process.
We work a lot on building brand within the bootcamp as well. Now that we're hiring, we're starting to build a bit of a reputation and by bringing people in to see our space, telling them about the projects that we do, I think that we're starting to generate a lot of interest.
Megan and Brennan, I want to talk about what goes into a technical interview for data scientists. What would I expect as a data science candidate?
Megan: I see employers do things really differently. There is a lot of overlap from coding interviews for software engineer roles to data science. I see most of our grads having to do some level of whiteboarding. They may not necessarily be coding on the whiteboard but instead walking through a solution, how you would approach it, and how you would get to an answer. At Metis, students do whiteboarding practice almost every day. They’re pair programming all the time at Metis, so they feel comfortable doing that with an employer on an interview.
We also see companies incorporating case studies into the interview process. Case studies are just a huge part of the data science world. Sometimes those are in the office, sometimes they’re take-home projects that the candidate has to be ready to present in front of an audience at the interview. Communication is such a huge part of the data science role, so candidates have to show communication skills, logic and technical skills, and also portfolio review. At Metis, students build five projects along the way so that they have this robust portfolio to show employers. I see a mix of those three things happening in data science interviews.
Brennan, of those three things: communication skills, technical skills, and portfolio, which stood out the most about the Metis students you have hired?
Brennan: I hate to give a floppy answer but it really is a mix of all of three. Our interview is a four step program. I warn our candidates that during our interview process, they may be asking themselves, "Am I interviewing for a software engineering job or for a data science role?” We really do test those Python and Scala skills in our candidates, but our interview process is pretty detail-oriented and by the end of it we have a good feel for their analytical abilities, their mathematical abilities and their culture fit as well. And we try to paint a nice, complete picture when making our final decision on our candidates.
Do any of the Metis students you’ve hired have PhD’s?
Brennan: Megan, correct me if I’m wrong, but I don't believe they do. The people that we've hired don’t come from traditional computer science background.
Megan: One person has a Masters degree in Math, which is relevant, but not computer science. Another person had a bachelor's degree.
Has it ever been a concern for the Capital One Labs team that those students didn’t have PhDs?
Brennan: Generally speaking, in our data science community here at Capital One, not many of them come from a traditional computer science type of background. Of our Ph.D.s, we legitimately have a Ph.D. in theology all the way through to astrophysics and everything in between. A few of those are computer science backgrounds but not all of them.
Brennan, how do you ensure that new hires at Capital One Labs are supported as they continue to learn after they had graduated from Metis?
Brennan: Absolutely- I think that's the hardest thing for me to portray to candidates as a recruiter. At Capital One Labs, we have a large community of data scientists all over the country- San Francisco, Chicago, New York, DC, Dallas- and that community of data scientists is really supportive. We know most of one another on a first name basis. We have our own internal Big Data Academy as well. We have meet ups internally where we all meet in one city and catch up with one another. Capital One is a great place to work as a data scientist for several reasons, but the one that's hardest to portray is the community within the Capital One culture.
Capital One is a really big company but as a data scientist it feels more like you're working at a big start up with around 100 to 200 people as opposed to a huge bank with 50,000 employees. They all know each other very well, have lunch together every single day, and travel to see one another all the time. It's a really tight-knit community of people.
Megan, as you build Metis's employer network, how important is it that your employer partners provide mentorship for your graduates?
Megan: That's something we definitely look out for, and we hope to partner with those types of companies. We see our students and our grads being selective for those types of opportunities as well. Unless they're coming to Metis with a lot of professional experience already under their belt – and we definitely do have that profile of a candidate – then they may be okay in a less mentorship-driven company. But to find an employer like Capital One Labs is just so awesome for our students.
We've also started working with employers on building out apprenticeship programs and that has been very successful. And really the model works. We have tried 8 to 12 week maybe even 16-week apprenticeships where they can come in, work on real projects for the team, and there's a heavy mentor component to it. They can get up to speed in more of a comfortable but accelerated pace, and when they come on full time they're ready to go from Day 1.
Do you see most Metis graduates going into straightforward Data Scientist roles or are there other types of roles that students can get when they graduate from Metis?
Megan: The title that we most often see is Data Scientist. We also see Data Analysts or some analyst position. Data Engineer is usually the third title we see.
What have you seen your most successful Metis graduates do differently that really sets them apart as candidates for data scientist roles?
Megan: First, how do you define “successful?” In my eyes it's a student who lands a competitive data scientist position at a company that they're super passionate about within the first month or two of graduating from Metis. When I see people following that path, they've been incredibly engaged during the bootcamp and also they're all-in with careers. They're just soaking up the advice and all the tidbits of information that we that we put out there.
The most successful Metis grads are juggling and balancing a lot of or spinning multiple plates at once. They're building their projects, they're learning, they're involved with the career team, they're getting their resumes together, they're interviewing. Juggling everything is a lot to ask, but they're able to handle it gracefully and confidently.
After Metis, they have a plan. They're not taking a few months to just relax, they're aggressively attacking their search and taking all the advice that we've given them and totally utilizing their network that we helped them build and just going after it. I see those people with the most offers, having the most options, and feeling most successful out of Metis.
Do you recommend that students start applying for jobs the second they graduate from Metis or should they wait a couple of months after they graduate to improve their portfolio?
Megan: I think personal comfort level factors in, but we see a lot of people starting to get a little antsy about their search around Week 9 of the bootcamp. They’re starting to think of their list of target companies to start applying to and researching. Around that time, they may start putting out some applications and start getting some coffee meetings with hiring managers. By career day, they're starting to more actively apply. I think that's a pretty good timeline to start things off.
Do Metis and Capital One Labs have a nice feedback loop? If you notice a new hire is lacking in one subject, are you able to give that feedback to Metis?
Brennan: Yeah, fortunately we haven't seen any gaps to relay back to Metis. Capital One has a relationship with Metis on several different levels. We partner with them in all kinds of different ways. So there’s a nice give and take between our relationship as far as helping them help us and vice versa.
Megan: We have a close partnership and it's been great to work with them. They've definitely given us some awesome feedback on career day and that has certainly evolved drastically over the couple of years that we've been running bootcamps. It's just awesome to get that advice because they're the ones that we're doing this for and their feedback is so important to us.
Brennan, will you hire from Metis in the future?
Brennan: That's the plan!
Megan, there’s a lot of talk about how to report outcomes and the methodology behind those statistics. Is Metis planning on publishing an audited report anytime soon?
Megan: We're definitely thinking about that very seriously. We are actually accredited by a company called ACCET and we have to go through an audit process frequently. We have to submit verified employment data once a year. Our numbers are very much accurate and if they weren't, they would shut us down. We are under very strict guidelines on how we report that data.
Brennan, last question. What is your advice to other employers who are thinking about hiring from a bootcamp or from Metis in particular? Have you found the secret sauce to navigating through the bootcamp world?
Brennan: The hardest part about hiring from bootcamps is that they essentially open the floodgates and all of us potential employers are all trying to find the top talent from the bootcamp all at once. The hardest part for us is having an interview process that selects the top talent and making sure that they are the right fit for our role, but then also being fast enough and agile to work with Metis grads as well because there's so much competition for this talent. My advice is to start early and build a strong relationship with the bootcamp and then build out a process that can effectively and quickly hire the right people.
Is there anything that we totally skipped over that either you Brennan or Megan want to make sure our Course Report readers know about?
Megan: It’s been great working with Brennan and the Capital One Labs team and we look forward to more partnerships and continuing the relationship and hopefully getting even more Metis grads onto their team in the future.