Welcome to the 2019 Predictive Analytics World (PAW) Conference Series. Recorded live in Las Vegas, this series is bringing interviews straight to you from exhibitors and speakers at this year’s event. In this interview, host Jamin Brazil interviews Mike Galvin, Executive Director of Data Science Corporate Training at Metis.
Find Mike Online:
Email: michael@thisismetis.com
[00:02]
Hi, I’m Jamin, and you’re listening to the Happy Market Research Podcast. We are live today at Predictive Analytics World. My last guest at the show is Mike at Metis. Tell me a little bit about the company.
[00:17]
Sure, so, as you know, that in analytics, data science talent… There’s a huge gap and there’s a large demand for it. So, that’s where we come into play. We’re a data science and analytics training company. We’re part of Kaplan. So, if you’ve heard of Kaplan, the global education company… We’re about six years old, launched organically, and we work with companies to upskill their staff, both technically and non-technically in kind of all things data science and analytics (data literacy, tools, machine learning).
[00:45]
That’s awesome. I actually think data science is the No. 1 job right now, nationally; I’m not sure if it’s global but certainly in the U.S. And there’s a big gap in terms of the need, the desire to hire from big companies and small companies, for that matter, and the available workforce. Sounds like you guys are playing a big part in, after people are hired, that subsequent improvements and ongoing skills training.
[01:15]
That’s part of what we do. There’s a little bit more. So, we have an accredited boot- camp that’s twelve weeks long. We have it in New York, San Francisco, Seattle, and Chicago. That is a retail consumer product for people who want to shift into or pivot their careers into data science roles.
[01:30]
How is that helping?
[01:32]
So, that helps with the data acquisition, intel acquisition pipeline at the entry level. Then, there’s the corporate training business, which is where I work. Within the corporate training business, we work with companies who not only upskill their existing tech talent in data sciences and in new areas and new tools and things like that but also their broader workforce; sometimes, even not technical in C-suite all the way down to individual contributors to build that literacy and fluency so that they can interact and collaborate with the data science teams more.
[02:01]
Oh, that’s very cool, very cool. Do you uh… On the engagement side of things, do you guys also have placement, help companies with placement or job candidate as you’re doing…? It seems like there’s that middle piece between people want to pivot their careers, right; so, you’re training at the data camps, etc. And then, all of a sudden, there’s like the need, which you’re training people internally, right; so, the space in the middle is, “I want to hire.”
[02:32]
So, not directly but indirectly. So on the bootcamp side, part of that is getting people jobs. So we have an entire career support team.
[02:40]
Oh, you do then.
[02:41]
Yeah.
[02:41]
OK, got it.
[02:41]
To get people into actual data science jobs. And over the past five-and-a-half, six years, we developed a huge network of hiring partners that we work with, and this ranges from Apple and Facebook to IBM and Ooze and all the way down to smaller companies as well, depending on who it is. We started with the bootcamp, but that hiring network is really how we kind of started getting to the data science corporate training space ‘cause we started talking to them and realized, “Hey, there’s not only this entry-level hiring partner…”
[03:12]
See, I think that’s really important because you’re offering really the whole product for the corporation, solving three distinct problems for them in that framework. And that’s a really powerful, awesome place to be able to sit, which again because of the sheer value and the network effect that you have because, obviously, you have the pivot people or whatever (the trainees, if you will) and then ongoing training inside of their corporate experience. So that sounds like a very compelling product.
[03:52]
It’s an entire end-to-end journey really.
[03:55]
Exactly, end-to-end. Right, totally, or end-to open end…
[03:58]
End-to open end. That’s right. I like that.
[03:59]
So, tell me a little bit. Do you have a favorite customer story?
[04:03]
Oh, wow, there’s so many.
[04:05]
Every customer story is a favorite, but you have to pick one.
[04:09]
Sure, so, I’ll just give you a recent example. So, we were working with a consulting company that works mostly in government and telecom. And one of their key issues was they’re primarily Excel users and some of the problems they were encountering required a little more advanced analytics but also, they had really large data sets that Excel couldn’t handle anymore. And so, that’s where we came in. And we put together a curriculum for them to train their consultants and principals and everyone kind of within the organization in Python to help add to their Excel workflow; and delivered the training a few months ago; and got some results out recently. And they have a 22.5-times increase in speed of developing… doing their analyses.
[05:03]
That’s unbelievable.
[5:03]
Yeah, that’s pretty cool because I always love to hear the impact that the training actually has because sometimes it’s hard to connect the dots to ROI. And in a case like that, it’s really apparent.
[05:12]
So, now, are you actually creating customized curriculum per customer or is it more black box?
[05:18]
It’s a little bit of both. So, we do have more what I would call off-the-shelf courses that we deliver, and it’s constantly evolving based on demands we’re seeing in the market. But we also work with companies to develop more custom, bespoke products depending on their needs.
[05:33]
Got it.
[05:33]
A lot of times we re-purpose what we have but contextualize it to their particular use cases. So to give you one example: Working with a client, who is a large Fortune 500 and financial institution, and they have a talent-acquisition pipeline problem; they want to create data scientists. So, what they’re doing is hiring STEM graduates right out of college and putting them through a twelve-week-long, on-boarding program. Now, we can re-purpose kind of our off-the-shelf, bootcamp curriculum for that, but what’s really important to a company like the one we’re working with is can we integrate in their use cases, their data sets. Some of their tools have some of their data scientists and machine learning engineers come in and contextualize it so they get a better flavor of the type of work that actually may be doing once they roll into their full-time positions.
[06:22]
That’s awesome. That is a great story. What do you think about the show?
[06:26]
It’s great. First time at Predictive Analytics World. So, so far, so good. Talking with a lot of great people, had a lot of great conversations. Pretty diverse crowd, which I love. I just gave a Lunch-and-Learn talk: (It went well) “Building Organizational Competencies for Data Science.”
[06:44]
I’m sorry I missed that. It sounds very interesting. They got me tethered to the booth here. So…
[06:52]
I’ll let it slide this time.
[06:53]
Thank you, thank you.
[06:54]
Had a great turnout. Lots of engagement. So it was an overall good session, and I’ve had a great time at the conference so far.
[07:01]
Good. Hopefully, it’s a lot of good leads.
[07:03]
Well, fingers crossed.
[07:05]
Yeah, yeah.
[07:05]
Only time will tell.
[07:07]
That’s the truth of it. That’s the truth of it. If somebody wants to get in contact with you, how would they do that?
[07:13]
Sure, so, one is our website: Thisismetis M – E – T- I – S.com. You can kind of explore the website and go from there. If they want to reach out to me about corporate training, you can reach me at corporatetraining@thisismetis.com, and then my email is Michael@thisismetis.com
[07:31]
Michael, thank you for being on the Happy Market Research Podcast.
[07:33]
Great, thank you.
[07:34]
Everybody else, I hope you found a ton of value. I certainly did in this episode. If you please take time, screen share, distribute it on social media. I would really appreciate it. Thank you, all. Have a wonderful rest of your day.
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