Is the role of a data scientist still a “sexy job” or has it lost a bit of its luster? And what’s more important for successful data leaders, deep data knowledge or business savvy?
Daniel Seymore is the Head of BI for Investec, a bank that is delivering out of the ordinary insights in the world of finance to help its customers create and manage wealth. One of Daniel’s career-guiding principles is to question the conventional, and on this episode of The Data Chief, he sheds light on some of these questions and shares how he is continuing to live by this principle to help Investec modernize its data capabilities.
Daniel and Cindi also discuss why the only constant in life is change, which means businesses must place a larger emphasis on upskilling workforces. Lastly, the two dive into why domain expertise might be the most important skill for any data leader.
- Domain expertise matters: The hardest pivot for most technical professionals is moving away from day-to-day technical capabilities and into a leadership role. Data science is an important part of any company’s toolkit, but great leaders should understand the problems they’re solving on a business level and be able to relay it back in a way everyone can understand.
- Fail quickly to learn and adapt: With any project, it’s good to have a plan but it’s also important to embrace the idea of failure. The faster you fail, the sooner you can learn and adapt your processes to succeed.
- Change management is about partnerships: Gone are the days when employees sit back and take every direction from their boss at face value. Successful change managers recognize the individual value each employee can add to a project. They treat it as a partnership. And this is benefiting not just immediate teams, but the business as a whole.
“The biggest thing is people think data science is just about the algos. The more algos you create, the better odds you’re going to get. As a matter of fact, that’s less than 5% of the entire job. The way that we approach it specifically in our space, we need to understand what is happening within your business areas. So domain expertise is by far the most important thing.”
“Four of the five projects that you run, there’s going to be a big failure. But the first one is the one that’s going to yield more money, and more value, to the other four. The main thing is you shouldn’t go through the same process in terms of how we’re ending it. You need to be explicit and actually explain it in business terms, “Why are we doing what we’re doing?” If we can’t do that, then it is just another technology thing we’re trying to add.”
“With any business project, if you don’t have buy-in with the right people from day one, if you can’t explain why we’re doing it in the right terms, and you don’t have the right matrix of success in place, as well as the right change management processes after you’ve done the implementation, things are not going to materialize.”
“The only constant in life is going to be change —and upskilling is something that needs to happen every three to five years, especially in the environment that we’re going to go into. You have to make sure that you’re flexing those muscles, and that you don’t get too stiff and too flabby.”
“What people do is they look at the quick wins, and that normally means either degrading technical date, or there’s workarounds in order to get to the quick wins. As long as you can stick to your processes, as well as your agreed patterns and frameworks and everything in how you want to solve it, that’s a massive thing. But you need to start. The quicker you can start, the quicker you can learn, the quicker you can adapt.”
Daniel Seymore joined Investec in 2016 and soon after got appointed to lead the Private Bank Business Intelligence team. Prior to Investec, Daniel worked at SARS as the Manager of the Performance Analytics team. His career has mainly been focused within the data realm with extensive experience within the fields of data analytics and decision sciences.
At Investec Daniel is responsible for operational and strategic management of the business intelligence and operational analytics capability within the Private Bank department. This includes identifying and implementing machine learning use cases and scaling the capability enterprise wide, refactoring and streamlining of data warehouse processes and implementation of self-service capabilities for end-users.