Christin's day-to-day work is all about finding creative solutions. For what exactly, you ask? For the development of algorithms. Christin is a Data Scientist in the Sensor & Algorithm Design department and programs algorithms for data analysis. Find out what exactly her job entails and why creativity is such an important part of her work in this interview. For more information, visit www.rosen-jobs.de/datascience.
Christin, you are a Data Scientist in the area of Sensor & Algorithm Design. Could you tell us what that means exactly?
I mainly deal with recurring patterns in our inspection data. For example, I look at what the inspection data of an industrial plant with corroded spots looks like. I use these patterns as a basis for developing various algorithms. By doing this, we make it easier for our data evaluation colleagues to analyze the collected pipeline data by having certain patterns already recognized by the algorithm and, if necessary, excluded. This is because in many cases there are several thousand locations in a data set that could potentially be an anomaly. But by no means every anomaly in the data set is also a defect. Since we operate in a very security-conscious environment, continuous validation of the algorithms is also one of my main tasks. This helps ensure that we do not create algorithms that inadvertently exclude relevant data. Using the data from our tools, we can also make statements about the performance of our inspection equipment and give out specifications and parameters for optimizing our tools to the appropriate colleagues.
What is your typical workday like?
In my project team, we follow the Scrum approach. That's why my day usually starts with the so-called "daily", a conversation with my colleagues in which we discuss what we achieved yesterday, what the plans are for today and what challenges may have arisen. To accomplish our actual tasks, we work in sprints. In the Scrum approach, these map out a defined period of time in which the team has to complete a certain work quota. We often have meetings to discuss the current sprint or the last completed sprint. As soon as smaller tasks are completed, there is typically a so-called "pull request". This is how you present new updates in the code to the team. The development team has the opportunity to give feedback, suggestions for improvement or hints about possible problem areas in the code before it is accepted.
To what extent are topics such as big data, artificial intelligence and high-performance computing constant companions in your everyday work?
Ah, the common buzz words (laughs). But yes: Big Data, Artificial Intelligence and High Performance Computing are extremely important topics for me and I have to keep them in mind constantly when developing algorithms. The data sets that our tools generate with their various sensors are huge and therefore a very good example of Big Data. High performance computing is an important topic, especially with regard to data analysis. After all, we want to develop algorithms that make our colleagues' work easier. That's why they can't take several weeks to analyze a data set. Artificial intelligence is also a topic that is becoming increasingly relevant to my work. Especially since the end of last year, this has been clearly noticeable and I find this development really exciting. However, other departments at ROSEN have been dealing with this topic for years.
What is your preferred programming language?
I originally started programming with Matlab in university, which is very similar to Python. Today I use Python for my work, because the language is mainly used within our department. However, other departments also use C++ and C#. I find that Python is a relatively easy programming language to learn and I enjoy working with it. In general, with programming languages, you have to understand the underlying logic once. Learning the different commands is then like learning vocabulary.
What qualities are particularly important in your job?
In addition to logical thinking, the ability to work in a team is particularly important. So far, I have only been involved in projects that were worked on as a team. The different team members complement each other well with their knowledge and skills - it is precisely this combination that usually leads to better results. Motivation, curiosity and openness for new things are also very important. Especially for the programming languages there are regular updates and new features, so I always have to keep up to date and try out new things. Creativity is also an important part of my work. The solutions to many problems are often not obvious, so I have to find a creative way to approach their solution.
What makes your job so exciting for you?
Definitely the creativity with which I find solutions in my day-to-day work. Precisely because there is not always the one right solution to a problem, the job is very exciting and extremely diverse for me. We always have smaller and larger goals that we want to achieve. Unlike projects in the daily business, however, our projects can sometimes span periods of several years. I'm particularly motivated by small challenges and goals that I set myself and work towards.
How did you discover your profession?
I studied mathematics at the University of Münster and already noticed during my bachelor's degree that I was particularly interested in applied mathematics. I pursued this topic during my master's degree and dealt a lot with the topic of image processing - primarily in the field of medical technology. During my studies, I was able to gain insight into the daily work at ROSEN through student jobs and internships and discovered that our tools do not actually generate anything other than image data. So the difference to the topics from university was not that big for me. That's why the job here at ROSEN was a perfect fit for me.
How have you developed personally and professionally during your time at ROSEN?
During my studies, I learned pure mathematics and dealt a lot with the topic of image processing. This is an important basis for the development of algorithms at ROSEN. At the beginning, however, I still lacked the physics background to understand our topics in their entirety. This background is very important especially for the interpretation of the results generated by an algorithm. I am very proud of the fact that I acquired this physical understanding myself and now fall back on it naturally.
But a lot has also happened in the topics of deep learning and machine learning in recent years, and I have always followed the developments with great interest. We are also moving more and more in the direction of software development and data engineering. That's where the boundaries become somewhat blurred with classic algorithm development. But that's precisely why I'm continuously learning new things.
What makes ROSEN special for you?
Definitely the colleagues at work. Even during my first internship at ROSEN, I noticed how important a good working environment is. If I have a bad day, I always know that my colleagues are there to support me or help me if I don't get ahead. I think we make a great team and we all complement each other with our background knowledge and expertise. Since my team is very interdisciplinary, I would even generalize this statement for ROSEN as a whole.
What are your goals for the future?
I am very excited about the direction in which the topics of deep learning and machine learning are developing. This field is incredibly exciting and so many interesting things are possible with these topics. That's definitely where I see myself in the next few years, and I generally want to explore the field around artificial intelligence further. That's not a problem here, because ROSEN supports such projects.
Thanks for the interesting insights into your daily work, Christin!