#125 Transitioning From Academia to Business – The Skills Gap with David Hardoon – Senior Adviser for Data and Artificial Intelligence
David is the Senior Advisor for Data and Artificial Intelligence at UnionBank Philippines. Concurrently David is an external advisor to Singapore's Corrupt Investigation Practices Bureau (CPIB) in the capacity of Senior Advisor (Artificial Intelligence) and to Singapore's Central Provident Fund Board (CPF) in the capacity of Senior Advisor (Data Science).
David loves the idea of programming logic. We have the ability to use information as mechanisms to assist us on a day-to-day basis. So, David was inspired to explore the possibilities of data. After high school, David considered artificial intelligence or astrophysics. However, he ended up finding a place that has a combined degree of computer science and artificial intelligence. In fact, he was the second student to complete the degree.
Then, David touches on the importance of knowing how to explain complex ideologies. Data scientists need to understand how to interpret these complicated ideas in the simplest terms. David has built his career on knowing how to simplify these things and use them. Data is all about identifying patterns. Many people believe that humans are unpredictable. However, we can be predicted. For instance, data science teams can tell a bank in advance how much cash the ATM will need on any given day.
Data science has to be pragmatic. If it's not practical, then it's research. David gives tips for people who are leaving the research side and entering the industry. First, think about the purpose. Is the intention to do research? Then make sure you go over the expectations. If the agenda is to find actionable items, then it's important to readjust the project's expectations. Constantly, researchers are trying to drive for the best algorithm. However, someone in the industry may be happy with a good algorithm rather than the best algorithm. Always bring it back to what you are trying to do.
Later, David reveals what he's most excited about in the banking industry. For one, COVID-19 has proven the importance of digital banking. There has been a 400% increase in digital banking customers. It's exciting that the digital banking journey started far before the pandemic. We want to be able to put foundational capabilities in place before there is a dire necessity for it. Digital banking can be a pleasurable experience. So, David is thinking about how to bring in people who are currently outside of the banking system and provide them with the safety and surety that banking offers.
Stay tuned as David gives his perspective on data governance – it's a mechanism that allows us to identify what we should and shouldn't do. In addition, David reveals his views on AI governance, and David explains how he balances all of his work.
Enjoy the show!
We speak about:
[01:15] How did you get started in the data field?
[02:30] What did your early career look like?
[06:40] What surprised you the first few years?
[13:45] How did you tackle both sides of the coin at the same time? (The problem of digitalization).
[17:00] Do you have tips for people coming from research into the industry?
[20:20] How does management in the industry handle all the different roles?
[24:00] Is data science a team sport?
[26:20] Tell us about what happened between your finance jobs.
[30:10] You chose to explore multiple areas in the data world. At what point was that a deliberate choice?
[34:45] What type of things are you excited about?
[37:45] Is there a period where you developed the love for data?
[41:10] How does it compare being inside a financial institution vs. being in a central bank?
[43:25] Do you see governance fueling innovation?
[45:50] Are there any initiatives that you are a part of? What is your opinion on governing AI?
[49:30] How do you balance all your work?
Resources:
David’s Website: https://davidroihardoon.com
David’s LinkedIn: https://www.linkedin.com/in/davidrh/
David’s Twitter: https://twitter.com/davidhardoon
UnionBank of the Philippines on LinkedIn: https://www.linkedin.com/company/unionbankph/
Quotes:
“I was called a geek many, many times in my life, so I’m going to own it now.”
“The objective is: how do you take these very complex ideas, and explain them in very pragmatic, very relatable terms.”
“I personally have a bit of an aversion to the term [data scientist], for two reasons: every scientist uses data, and it’s just too generic.”
“We need to also equally realise when data isn’t relevant, … a process is what’s required.”
We are now on YouTube! Watch the episode here: https://youtu.be/C3yQbUMcXhY
And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us.
Thank you so much, and enjoy the show!