How are projects usually structured and how does the composition of an analytics/data science team look like?
In our projects we usually work in a kind of triad: A project manager with expertise in the respective specialist area coordinates and controls the project. A hybrid consultant represents the AI & Analytics competence of our team in the project. Depending on the situation, this function can be provided by a data analyst, a data engineer, a data scientist, an IT architect or an AI specialist. In the end, we work together in a tandem of professional expertise in the field and technical expertise and have had very good experiences here. Our department can also be seen as a kind of cross section, since our goal is to set up projects from all business areas in accordance with our data generation and usage standards.
Which skills would you regard as vital for your current job role?
For my current job as head of the Center of Competence, above all I need to communicate clearly and precisely; the subject is often not trivial and therefore requires a lot of communication and transparency towards our internal and external customers. It is also important not to lose sight of the big picture. What really generates added value and what doesn't? Of course, our field of activity is very technological. That's why a certain joy in dealing with technology, complexity as well as figures and data is also required.
What was your career path? Which steps gave you the most important learning experiences for your career?
After my business studies, my path led me directly to an automobile manufacturer. At that time, digital business was growing rapidly, so I had the opportunity to work on exciting digital topics in the automotive industry right from the start. Here we learned above all to place the wishes of our customers at the center of our actions. Over the next few years, I was able to deepen my experience from different departments and perspectives on the subject. I have always enjoyed various topics and challenges very much, which is why after almost 10 years I decided to switch to the internal management consultancy of another automobile manufacturer. Here I first worked on the subject of Digital Business & eCommerce before I had the opportunity to set up a team of specialists on the subject of data and AI at two locations.
How do you see the development of data science/analytics over the next years?
For me, a data-driven culture and the right mindset are the key drivers for the future in the coming years. This means that more and more data will be collected and processed. This makes it all the more important to identify the relevant data and use them to make the right deductions for the further development of business and to be able to address customers in a targeted manner. In my view, data science and data analytics will become the central job roles in the coming years, across companies and industries. Data will be the USP in the future. That's why I can only encourage you to get acquainted with the subject.
Which three pieces of advice would you give to aspiring data scientists?
Before starting your career, gather experience from different industries and companies, do not commit yourself to a single technology and never neglect lifelong learning. This will prepare you very well for all future challenges.