Hiring From NYC Data Science Academy – Ben Reid of Elasticiti

This article is contributed by CourseReport, a third party website which specialized in covering bootcamp stories.

Ben Reid is the founder of Elasticiti, a tech services company that builds advanced advertising analytics SAAS systems for online web publishers. His team uses data to help companies make informed decisions, so Ben sees NYC Data Science Academy graduates as a fantastic talent pool. We chat about ramping up bootcamp grads, his experience with their first bootcamp hire, Sara, and why Elasticiti will continue to hire from NYC Data Science Academy!

Q&A

Tell us about Elasticiti. Who are your customers and what does your team do?

Elasticiti is a tech services company and we’re focused on helping digital media companies develop really top tier analytic solutions, using a mix of open source tools and their own choice of enterprise-grade technology. We work like a design or architecture firm would to take a raw idea to the next level of focus and strategy. We work in a very rapid, iterative fashion so that people can quickly incorporate information and turn it around in a new draft; that’s key to our process.

Are most of Elasticiti’s employees data scientists?

It’s a mix. We are thrown all sorts of different tasks, some are more in the data engineering realm, some are predictive in nature, a lot of them are visual and design driven. Part of the attraction of the data science background is that versatility in that broad skill set.

How did you get connected with NYC Data Science?

I’d been to three or four meetups hosted by NYC Data Science Academy before I realized we should be working together. Vivian and Janet are really talented and impressive so the conversation progressed from there.

We were looking to expand our hiring profile to include career changers. That fits the profile of someone coming out of NYC Data Science Academy. Our team has a lot of people who are much more senior in their career so this is an interesting complement to it.

What was your impression of the NYC Data Science graduates? Were you impressed?

The other motivating factor for hiring from NYC Data Science was the caliber of the candidates. We went to a couple of their showcases and saw some of the projects that they did, and most importantly, how they thought about the project. The end result is important but equally important is how they worked through all the challenges, what they personally thought was interesting about those questions, what they included/excluded, etc.

It definitely feels like the students there are of a pretty high caliber even before they come into the program. The school has only done a couple of cohorts so far, so the fact that they’ve been relatively exclusive in who they accept is a good sign.

Other than NYC Data Science Academy, how do you usually hire for the analyst roles on your team?

The most effective hiring method I’ve seen is through meetups and networking. You can go to a bunch of database meetups or Python meetups and after a while, you’ll meet the types of people who you need to hire.

What does the relationship between NYC Data Science Academy and Elasticitilook like? Are you paying to hire their graduates or is it just a mutually beneficial relationship?

Right now, there’s no referral fee or money changing hands. We seem to have a mutually vested interest in people graduating from the academy and finding careers.

Tell us about your first hire from NYC Data Science Academy.

We hired Sara Zeid for a couple of reasons. Firstly, she had relatively strong domain experience and had a good foundation in media. The other reason is that she had two degrees in social sciences. A lot of the way we look at the world in media relies on knowledge of sociology and economics so the fact that she had formal training in that was definitely attractive. Prior to the Academy, Sara didn’t have much technical experience, which really for us was neither a pro or a con. We felt that NYC Data Science would provide the broad foundation and we would fill in specific applications after that.

I love that, because I hear a lot of skeptics say; “How can an English or Econ major transition into a technical role?” In reality, those applicants are really strong because their past lives intersect with these new technical skills.

Absolutely. For what we do at Elasticiti, which is very prototype and idea driven, the way we think about problems is central. That willingness and that competence to tackle new things is really what we’re looking for. We can throw Sara a 19-gig file and she’ll tear through it in any number of applications to get down to another data set, and start quickly moving to interesting cuts of the data or finding trends within it to start the conversation with the business.

New perspectives are a great complement to the existing team. A lot of us have been in media for a long time and having someone come to the table and say “why is it done that way” or “that’s similar to something we tackled in week 13” can often bring new thinking to a project.

What kind of mentoring or onboarding is important for a bootcamp graduate?

We do a media 101/102/103, a lot if which probably doesn’t stick because it’s pretty vast, but you want to get an overview of the cosmos. Your project is going to dictate which part of the media universe is really important. We certainly don’t want our new hires to be overly spoon-fed. We want people to be a little self-motivated, too. Media is a large and interesting animal; understanding the habits and traditions of this industry is definitely critical. In addition, for those newer to the workforce, we teach some ‘soft’ skills too which can play a role in progressing a project. These can range from presentation skills, to running effective meetings, and asking questions in a way that gets the most useful response.

Do your other employees have CS degrees?

We actually haven’t hired anybody with a formal CS background. Everybody comes to the table with some other social science or even liberal arts background but along the way has acquired the necessary technical skills. Some have MBAs, a number of folks have other social science backgrounds like Economics. The common thread is genuine interest in problem solving and the tools used (R/Shiny, Python, Postgres etc).

Do you have a feedback loop with NYC Data Science at all? Are you able to influence the curriculum based on your own needs?

I would say that feedback loop is nascent, but we have had some conversations along that line. We’ve also talked about giving NYC Data Science cohorts some sample projects along common industry challenges and mocked-up data sets but we haven’t done anything yet. Client privacy is absolutely critical so their data is off-limits. That said, media is a big hiring industry and we’d love to expose some of the canonical media problems and data science applications. There are a ton of great Machine Learning and Time Series Forecasting examples.

How early on do you get to start interacting with the students? Are you meeting them midway through or at the very end?

NYC Data Science Academy makes them available to us so we talk to them midway through. Not in the sense of “Hey, I’ve got a job for you” but I view everything as relationship building and credibility is so key. We get to talk a little bit about what motivates them and what they’re after and vice versa, and that will grow or not grow as is natural. Those types of things tend to evolve over weeks, if not months.

Will you hire from NYC Data Science Academy in the future?

Yes, we’re already talking to a number of students from the cohort after Sara’s for potential candidates on potential roles. So far, I’m very happy with Sara. There are a lot of interesting people coming out of that group and we’re definitely interested.

NYC Data Science also has a Data Engineering class, and I’m interested in those graduates as well. It’s great to be conversant and capable in both back-end and business analysis but we definitely have a need for people who are really good at what I call “beating up the data” in service of multiple data scientists and analysts.

Would you recommend hiring data scientists out of a bootcamp? Are there types of companies that you would not recommend to hire coding bootcampers?

It’s hard for me to answer the negative side of that for other industries or other types of companies. For us, the attraction was and probably will remain that bootcamp grads come to the table with a wide range of foundational skills and they may come to the table with more advanced niche skills that they want to build upon. That’s what really works for us.

If you are interested in learning more about NYC Data Science Academy check out reviews on Course Report, or find more information on the NYC Data Science Academy website.

 

Vivian Zhang
Vivian Zhang
Vivian is a data scientist who has been devoted to the analytics industry and the development and use of data technologies for several years. She obtained expertise in data analysis and data management as a Senior Analyst and Biostatistician at Memorial Sloan-Kettering Cancer Center and Scientific Programmer at Brown University. She is the co-founder of SupStat, founder of NYC Data Science Academy and the NYC Open Data meetup. She earned her M.S. in Computer Science and Statistics and B.S. in Computer Science. Vivian is a programmer and all-around dataholic, and considers herself a visualization evangelist.

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