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 bit about Matheus:
I’m Matheus Torquato, currently a Senior Data Scientist at JLR (yes, the fancy car people!). My background spans both industry and academia – I previously worked as a research engineer developing collaborative projects between universities and companies. I hold a master’s degree in computer engineering from UFRN, my beloved alma mater.
How did you start out in your tech career?
I’m one of the lucky few who already knew what I wanted since I was a child. As a kid and teenager, I spent countless hours in front of my PS1 and later PS2. I’ve always loved technology.
Choosing to study computer engineering at university wasn’t a difficult decision. During my university years (starting in 2010 – yes, I’m officially ancient in tech years), I was really fascinated by anything AI-related, back when it wasn’t as trendy as it is nowadays. Since then, I’ve never stopped working in AI – through multiple internships, exchange programmes, industry placements, my master’s degree, first job, and beyond.
What are the signs of success in your field?
Bear with me – I’ll get a bit philosophical here, but success is subjective and varies according to what it means for each person. Success for one person might be spending the maximum amount of time with their dog after work; for another, it could be earning as much money as humanly possible (no judgment here, we all have bills to pay).
Right, with that existential crisis out of the way, we can now focus on success in data science. I would say that success in data science is about delivering value (this can get philosophical as well) through actionable insights that help the decision-making process. From the latest and greatest generative AI model to the simplest linear regression model, a data scientist can be successful regardless of the complexity. It’s not about the size of your model, it’s how you use it!
What is the best and worst thing about your job role?
The best thing is definitely seeing successful outcomes – the value delivered from data science-driven initiatives. Unblocking that process or achieving that improvement using data and technology where other tools or methods couldn’t. It gives data scientists that superhero feeling!
The worst thing is probably being blocked from achieving what I’ve mentioned above. The adoption of the latest disruptive technologies isn’t always as fast as we’d like. Being blocked due to users’ fear of adopting a new method or process can be quite frustrating. This is especially true in the most traditional sectors of the economy, where the aversion to adopting innovation feels even stronger.
What can you advise someone just starting out to be successful?
Get things done.
Less talking, more doing! The number of free resources, materials, courses, services, and tools available today is an absolute paradise for anyone wanting to build a career in tech. Seriously, we’re living in the golden age of “learn literally anything on YouTube”!
Go out there and explore, create, experiment, deploy, break things (accidentally, please!), fix things, train models, and build a little portfolio of your projects – this could be extremely helpful to you in the future. The best way of learning is definitely by doing it. Trust me, you’ll learn more from one spectacular failure than from ten perfect tutorials!
How do you switch off?
Outside work, I try as much as possible to stay away from the tools and topics I work with. Most times I fail miserably due to the fact that I’m passionate about what I do at work.
Outside tech, you’ll find me daily at the gym, in a café reading something, or just chatting with friends. I’ve started venturing into writing, which is something far more complicated than anything I’ve ever done, but it’s also very exciting.
Oh, and music. Always music. At work, at home, at the gym, driving, in the shower – everywhere.
What advice would you give your younger self?
Very similar to what I said about advice for someone just starting out in tech: get things done, network, and have fun! Work takes up far too much of our lives. You’d better do something you really like, or at least something that doesn’t make you question your life choices every Monday morning!
What is next for you?
Looking forward, I’m curious about how this new boom of generative AI tools and models will affect the entire tech sector. There’s a lot of talk (and hype, let’s be honest), but I’m excited to see how this will transform the way people work, explore creativity, and the effect it will have on our lives and the products/systems we create.
Personally, I’m really keen on continuing to explore this new hobby of writing. I’m curious to see if this is something that will die down in a few months or perhaps something I can actually maintain. Let’s see!
If you could do anything now, what would you do? Why?
I’m really passionate about academia, so one day I might start a PhD or EngD. This sits somewhere between career-wise and personal, I’d say. Call me crazy, but yes, this might potentially happen. Because apparently, I enjoy intellectual suffering!
I’d love to get more involved in external discussions about AI and tech. It’s incredible how much one can learn by chatting with clever, like-minded people who are into the same things you are. Guest lectures, presentations, conferences, symposiums, hackathons – sign me up!
What are your top 5 predictions in tech for the next 5 years?
- Over-reliance of people on technology (AI assistants) – We’ll all become helpless without our digital butlers!
- AI agents sometimes bringing more problems than they actually solve
- Quantum computing breakthrough?
- Hints of Artificial General Intelligence (AGI)
- Printers will continue being difficult to use and behaving strangely at the most unexpected times- Some things never change. Printers are the constants of the universe! (This one’s not really a prediction, more like a universal law of physics at this point!)
Watch Matheus’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!