Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!
A data professional who has turned their hand to Data Science, Analysis, Data Engineering and most recently Machine Learning Engineering. Jack of all trades, master of none!
How did you start out in your tech career?
I managed to get a job on a Data Warehouse project in government in around 2001. From there I progressed through MI Development, Statistics, Analysis and finally into AI.
What are the signs of success in your field?
That’s a tough one since success is subjective! In my current job (Machine Learning Engineering), I encourage my team to be thorough and build things “for the ages” so success for us means the services we build do the job they’re intended to with minimal intervention required from us.
What is the best and worst thing about your job role?
Best: I have a lot of freedom in terms of “how” to solve problems and challenges. This means some discussion with the team, coming up with a plan and design and then executing that. When it all comes together and works, it’s a great feeling. Processes can be powerful things.
Worst: Working with Data Scientists!! Haha, no I’m kidding obviously. I’m a leader and manager now, so the time I spend writing code has shrunk. That makes keeping my hand in on the technical side of things much harder, especially considering that AI is moving at an astonishingly fast rate.
What can you advise someone just starting out to be successful?
Don’t neglect your soft skills. For example, being able to communicate technical concepts clearly and in simple terms is probably the most important skill I have.
How do you switch off?
Being with my baby girl! She’s just turned 1 and a positive thing about the COVID pandemic is that it’s made working from home the new norm, which means that I get to see her a lot more than I would otherwise. I took her out for pizza and to a museum the other day. We had a great time!
What advice would you give your younger self?
Get good at learning. I’m presented with problems I don’t immediately know how to solve on a daily basis and being able to quickly figure out the background and solve things is vital.
What is next for you?
As I said earlier, staying abreast of AI and tech is difficult. I’m hoping to transition into a more “upstairs” role with more strategy, process development and leadership.
If you could do anything now, what would you do? Why?
Speak fluent Italian! My wife and her family are Italian and although I’m learning slowly, it would be great to be able to have proper conversations without asking what some words and phrases mean.
What are your top 5 predictions in tech for the next 5 years?
Five predictions? That’s a lot! I’ve been in the game long enough to know that you can’t make predictions in tech, but I’ll make three…
- More SAAS dedicated to AI. I think that companies have realised that having dedicated DS teams to re-invent the wheel is hit and miss, and that buying in proven AI services for specific jobs (e.g. marketing, churn, segmentation etc.) is a more cost-effective way forward.
- Less AI and more Analysis. I think a lot of places have also realised that jumping on the AI bandwagon before they were really ready has led to it not delivering the benefits they would have hoped. They’d be better served trying to make data more a part of their everyday decision making.
- Expect more huge advances in NLP. ChatGPT is blowing up my LinkedIn feed at the moment.
Watch Tom’s session at the Data Science Festival here.
Thank you to all our wonderful speakers for taking part in our Speaker Spotlight!
Want to become a DSF Speaker? Apply here!