How physics took Radhika Feron from curiosity about the universe to protecting critical systems through data science.

There’s a moment in every emergency call when reliability matters more than almost anything else. Someone reaches for a phone in crisis, expecting the system behind it to work instantly, invisibly, flawlessly.

For Radhika Feron, Senior Data Scientist at Telstra in Melbourne, helping make those systems more reliable is part of everyday life. Using machine learning and advanced analytics, she works to identify issues before they escalate, helping teams respond faster and with greater confidence in moments when every second matters.

It might sound far removed from lecture theatres and quantum mechanics. But to Radhika, the connection is obvious.

“Physics got me here by teaching me how to think, not just what to learn,” she says.

That mindset, breaking down complexity, questioning assumptions and looking for patterns hidden inside noise has shaped every stage of her career.

Physics was never a surprising choice for Radhika. Growing up surrounded by physicists and engineers, curiosity was simply part of everyday life.

“I loved physics in high school and it quickly became my favourite subject,” she says. “I was naturally curious about how things work, and physics gave me answers to the secrets of the world.”

That curiosity led her to study a Bachelor of Science majoring in Physics alongside a Bachelor of Computer Engineering (Honours) at the University of Newcastle. At the time, academia seemed like the natural next step. PhD opportunities in both physics and electrical engineering were on the table, including continuing research in electromagnetic modelling.

Having already achieved First Class Honours in Computer Engineering and a Distinction in Physics, further recognition soon followed for Radhika. She was awarded the Faculty of Science Medal, the Faculty of Engineering Medal and, most notably, the University Medal for Computer Engineering at the University of Newcastle; an honour awarded to just one graduate per degree each year in recognition of exceptional academic achievement.

An unexpected career turn

Radhika joined the Telstra graduate program and discovered data science, a field that allowed her to combine analytical thinking, systems engineering and problem-solving in a fast-moving, real-world environment.

“One of the most unexpected turns in my career was moving away from physics and engineering into data science,” she says. “It wasn’t something I originally planned, but it allowed me to apply the skills I loved in a much more dynamic and applied way.”

Today, no two days look the same. She leads end-to-end data projects, working with stakeholders to understand operational challenges and translate them into solvable problems. Some days involve exploring large datasets and engineering machine learning models. Others are spent mentoring colleagues, leading workshops or building broader data and AI capability across the organisation.

What ties it all together is impact

“By improving the detection of issues in emergency call services, my work directly supports public safety,especially in critical systems like emergency call services,” she says. “It helps ensure people can access help when they need it most.”

Alongside operational systems, Radhika also contributes to early-stage research exploring quantum-inspired approaches to forecasting and anomaly detection; work sitting at the intersection of physics, AI and emerging computing technologies.

For her, this blending of disciplines is one of the most exciting parts of modern physics.

“The combination of physics with AI, data science and advanced computing is accelerating discovery in ways we couldn’t before,” she says. “We’re seeing quantum computing move from theory into real-world applications, and that has the potential to fundamentally change how we solve complex problems.”

Even outside traditional research environments, physics continues to shape the way she approaches the world.

Many of the skills she uses daily: systems thinking, modelling uncertainty, identifying meaningful signals in noisy environments and testing hypotheses, all coming directly from physics training.

“Physics teaches you to break down complex systems into fundamental components,” she says. “That’s incredibly valuable when working with interconnected networks and large-scale operational systems.”

Technical knowledge alone isn’t enough

Radhika believes communication, collaboration and adaptability are just as important as scientific expertise, especially in industries where physicists increasingly work alongside engineers, product teams, designers and decision makers.

That adaptability also applies to career pathways themselves.

“You don’t need to have your entire career figured out while you’re at university,” she says. “I started with a plan to do a PhD in physics and ended up in data science, and I love the career I’ve built.”

Her advice to students and early-career physicists is simple: don’t wait until you feel ready.

“It’s completely normal to feel out of your depth,” she says. “That feeling doesn’t mean you don’t belong. It usually means you’re growing.”

“Take opportunities before you feel fully prepared. Confidence comes from doing, not from waiting.”

“Outside of my regular project work I also build data capabilities across the organisation by leading community of practices, organising Data & AI hackathons[JT1] , and running machine learning workshops.”

Visibility and diversity in physics also matter deeply to her. Not only because representation helps people imagine themselves in science, but because different perspectives lead to better solutions.

“Every person sees problems differently,” she says. “When you bring those perspectives together, you get more creative and innovative outcomes.”

She’s particularly passionate about challenging the stereotype that physics is only for a narrow type of person, or that it only leads to academia.

“Physics is for anyone curious about how the world works,” she says. “And physics skills are used everywhere; across technology, healthcare, finance, communications and beyond.”

Despite working in data science, Radhika’s fascination with physics itself has never faded. Especially quantum mechanics.

“Quantum mechanics fascinates me because it challenges how we intuitively think about reality and certainty,” she says. “The world isn’t always binary or fixed; it holds infinite possibilities at once.”

It’s a fitting reflection for someone whose own career path didn’t follow a fixed trajectory either.

Physics didn’t just teach Radhika equations or theories. It gave her a framework for navigating uncertainty, solving problems and staying curious enough to explore paths she never originally planned.

“Say yes to opportunities that come your way and treat them as experiments. You say yes, you try, and the worst-case scenario is you’re still learning something.”

This article was first published in May 2026, as part of the AIP's #PhysicsGotMeHere series, featuring some of the career pathways that have been made possible by a physics degree.