#196 There is more to data science than just the data! with Edward Chenard, the Senior Director of Data Science and Analytics at Shipwell

“Data engineers are like plumbers,” Edward Chenard, the Senior Director of Data Science and Analytics at Shipwell, said in this latest episode of the Data Futurology Podcast.

By that, Chenard means that data scientists are excellent at analysing what’s coming through the proverbial pipes, but if the “pipes” break for even a couple of hours the costs can be in the millions of dollars, and so you want specialised data engineers operating in the background, maintaining the stack and being the unsung heroes of the data practice.

This is just one insight on building effective data teams that Chenard shares on the podcast. In this in-depth discussion, he also:

  • Highlights the changing dynamics within teams post COVID-19 and how interactions have changed with working from home.

  • Discusses the disconnect between leadership and data scientists/engineers, and how many data scientists come to realise that their interests lie outside of leadership.

  • Talks about finding ways to develop confidence into younger data professionals.

  • The increasing value of humanities expertise in data.

Finally, Chenard shares his three key personality qualities that allow someone to succeed in data-based roles:

1) Creativity. If you don’t look at the space as a creative endeavour, you’re not going to be happy.

2) Curiosity. If you’re not naturally going out there and looking up stuff, going down different rabbit holes you’re not in the right mindset.

3) Openness. You need to be open to other perspectives – including those you don’t agree with – to be able to see the opportunities that come from data.

Tune in for these insights, and many more, around the dynamic roles and exciting opportunities facing data scientists ahead.

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“If you want to move fast, you want to move smoothly, you need data engineers” - Edward Chenard, the Senior Director of Data Science and Analytics at Shipwell

WHAT WE DISCUSSED

0:00 Introduction
02:36 Could you tell us your role in the organization at the moment?
04:27 How do you find the process of getting support and investment for the engineering space?
07:12 I know that you've focused a lot on managing remote teams, how has the last couple of years been?
09:57 What are some of the ways that you've started to do in a virtual environment with your teams?
24:22 What do you think about how we can better prepare leaders in our space?
31:13 How did you find the transition into the analytical side?
38:31 What are some things that you think more people should be thinking about? Or a different perspective that people don't usually take when approaching a design of their career? Something that you think you've seen people benefit from? What would be something they should be thinking about?

EPISODE HIGHLIGHTS

  • But we look at ourselves as sort of that forward-looking team for the rest of the organization, we're really trying to figure out, hey, what's the future here? And how do we help build that? And how do we help our customers achieve what they're looking for through could be something as simple as just automating a process or helping them predict. How's their market going to perform in the next six months.

  • I like to make the distinction that the data engineers are the plumbers, they're keeping everything working. Think of the data scientists and the analysts as the scientists doing the chemical analysis of what's flowing through the pipes

  • I realized I have to pay a lot more attention to the mental health of my team. And I also have to get a little bit more personal with my team and just understand what it is they're doing.

  • Hey, don't get too close to the team. They gotta respect you don't be their friend. You know, you're the boss. So keep a bit of separation. Now. It's like, hey, I need to ensure that this person is feeling okay

  • And it's just coming up with what's that personal roadmap for them. And also giving them recognition in front of the rest of the company. We do all hands every two weeks. And I'm always saying like, hey, you know, we had this great performance, look at the savings, we got our customers on this one product, by the way, that was our data scientist Drew, who created that algorithm that that got these customers a savings

  • A lot of people in the data and analytics space, make the mistake of thinking that leadership is just an extension of what they're doing as an individual contributor.

  • No matter what level they're at, to be successful in this space, I think they need three things, whether you're the leader or a junior data scientist, first is creativity. The other is they have to have curiosity. The last one is also openness and openness to other perspectives.

  • Never start with the negatives. As I look, there are a lot of ideas I worked on where if you looked at it, 90% of it just sounds like a crazy stupid idea. But that 10% wasn't. That's where the money was.

  • You can sit here and say I did this, I did that. But if you start throwing out numbers and say, here's the impact, here's a result. I was like, that's going to do the selling for you. And it's going to be a lot easier for you.

  • Our key metrics are focused on how are we influencing our customers. We don't add anything about uptime, how fast the model runs, or how many story points or features we did? I'm like, nobody cares, no customer cares.

  • Data science is a tool I use to help create experiences, if anything, I craft experiences. And I help people find the experience that they're looking for.


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