Julian looks relaxed and laughs as he sits in front of two monitors displaying a dashboard with various analytical data.

ZEISS Stories | Julian

Tracking down
data

Digital Innovations

Forehand or backhand, topspin or sidespin, counter, flip, block: in table tennis, the right technique can make or break the match. Different strike techniques impact the ball's trajectory, rotation and speed. Julian has been playing this sport for half his life, and he leaves nothing to chance. He categorizes and analyzes the serves, visualizes the data and incorporates his findings into his next game. "There are limits to the sporting triumphs you can achieve with this technique," Julian says with a grin.

It's totally different when he's at work: as a Data Scientist at ZEISS Research Microscopy Solutions, Julian's feel for data is enormously important. The department supports users of electron, light and X-ray microscopes in research and industry as well as in the life, materials and earth sciences. If equipment requires maintenance, field service technicians visit the customer and do the work on-site. Some of the high-end microscopes are connected to software that sends machine data to ZEISS. This is where Julian comes into play.

Julian, an employee, is sitting at a laptop, grinning and typing on the keyboard.

Insights with major potential

He collects and analyzes submitted data, such as the microscopes' temperature values, currents and voltages. He creates graphs and uses algorithms to search for anomalies and correlations. "These assessments enable me to predict factors such as component wear," he says. If Julian's information suggests there could be further benefits, he develops machine learning or deep learning models, for example ones that can inform a field service technician in the event of anomalies.

His team, adjacent departments and customers benefit from these valuable insights: they make the field service technicians' work easier to plan and more efficient. Microscope downtime can be predicted, reduced and, increasingly, resolved remotely. "This takes our customer service to a new level," Julian says with pride. His work is also incorporated into the development of new equipment, while the Sales team makes use of insights into microscope user behavior.

If the required data are unavailable or their quality insufficient, the results of my work will also be unsatisfactory. So it's important to coordinate with product development teams on the requirements and the collection of relevant data early in the process.

Julian Data Scientist

Goal in sight

Julian's biggest challenge: success in data science depends on the available data. He explains: "If the required data are unavailable or their quality insufficient, the results of my work will also be unsatisfactory. So it's important to coordinate with product development teams on the requirements and the collection of relevant data early in the process."

Julian has found his calling. But he couldn't have predicted it. "I first discovered the world of data during my dual study program at ZEISS," reports the former computer science student. "Topics such as deep learning, robotics and virtual assistants also intrigued me," says Julian when asked why he then chose to do a master's in machine learning and data analytics before returning to ZEISS in his new role as a Data Scientist. And his professional development did not stop there – he's got his sights set on further expanding his knowledge through the ZEISS Expert Ladder. He knows his chances are good because he's done the analysis.