Dr. Leonardo Di Matteo - Senior Data Scientist and “puzzle-solver”
People often ask me why I moved from academia to healthcare and from particle physics to data science. After obtaining an MSc in Milan, I did my PhD in particle physics at CERN, the European Organization for Nuclear Research. Those were exciting times. You must have heard of the Higgs Boson, that elusive elementary particle in the Standard Model of particle physics. It was first thought to exist in the 1960s but only recently has its presence been confirmed – and I was privileged to be part of that team. In my post-doc at MIT, I was looking for dark matter, the ‘Holy Grail of particle physics.’ After that, I kept on looking for the next challenge – and joined QIAGEN as a Senior Data Scientist in June 2015.
So what’s the link between particle physics and QIAGEN? Well, particle physics is basically all about interpreting masses of data and searching for anomalies. That gave me a good skill set for my present job. At CERN and MIT, I acquired the intellectual techniques you need to tackle a project in the right way – and those techniques are the same wherever the ‘Big Data’ comes from. I actually prefer to talk about ‘Smart Data’ because the focus is on handling data optimally rather than blind processing. My current job involves extracting insights from the masses of data we generate every day, e.g. about customers’ purchasing behavior. We have developed techniques to spot anomalies in data and play them back to our sales people. Our recently introduced, award-winning Sales Cockpit, an evolutionary operational analytics tool, is an incubator of new ideas and generator of insights into sales and customer behavior data. That way, we can tell our sales reps what a customer might be interested in buying, for example, or look at what customers have published in the research field, interpret that data and then predict their potential demand. We’re turning data into customer and business value.
And where are we heading? One way to look at data is to think of it as a deep, dark pool rich in insights awaiting the right analyst to be revealed. I always get amazing help from data visualization, which acts like a flashlight in this analogy and guides our research in the midst of such deep waters. Our vision is inspired by other data-driven giants like Amazon, where the challenge of analyzing vast amounts of retailing data was overcome so successfully it gave rise to a new business model where digital services play a primary role. I believe that QIAGEN is taking huge steps in digitizing the entire value chain and moving into a best-in-class position in our industry. We want to be the spearhead of QIAGEN’s new data-driven services that will improve our customers’ lives in the future, and ultimately empower them to access new scientific insights hidden in the many data sets collected by using our products.