A flying start as a Data Analyst, that’s exactly what StackFuel’s Data Analyst alumni Siegfried Bondarenko has managed to do. Siegfried is a Berliner, trained as a medical technician and physics engineer. He encountered a job market hit by COVID-19 in 2020, so he decided to adapt to this situation and broaden his horizons with the help of a data analytics course. The job offer came before he had even received his certificate of completion. In October 2021, he will start his new job as a business data analyst. In the following interview, he explains how he succeeded and how he experienced the course at StackFuel.
Hello Siegfried, thank you for sharing your success story with us. What can you tell us and our readers about your career so far and your decision to continue your education?
I have always been very interested in technology and science. Building on my training as a medical technician, I studied physical engineering in my bachelor’s degree and later photonics in my master’s degree at the Technical University of Wildau. During as well as after my studies, I was employed at a Berlin-based, high-tech startup and then moved towards applied science at an institute for laser and plasma technology.
On the one hand, I had been looking for a challenge away from the lab for a while, thinking mainly of a job in industry or public service, but on the other hand, I saw a need to broaden my horizons and adapt to the changing job market due to the COVID-19 crisis of 2020 and 2021.
A long phone conversation with a friend about my career prospects during the covid crisis brought me to the topic of Data Science. When that keyword came up, I knew that was exactly what I was looking for. That same day, I came across StackFuel during my online research and the info brochure’s graphic design alone made the courses appealing to me. Of course, the course content was at the forefront of my decision, andthe programming language Python piqued my interest in particular, as I’ve always been keen to learn it.
Where did your interest in data and programming with Python come from?
Data is powerful, but worthless without processing and analysis. I find it exciting to find patterns, structures, and dependencies in data sets and thus make them usable in the first place and generate added value from them. In addition, you can use successful visualization to transport and simplify complex relationships, so that people from outside the field can identify and understand the connections. This is what makes interdisciplinary work possible in the first place.
Did you have any reservations about working with data, programming and higher mathematics?
I was certainly most scared of programming, because although I’m a physics engineer, I never learned programming in my studies. I had difficulty teaching myself programming with YouTube tutorials and without applying it directly. In this regard, the course at StackFuel was a gamechanger for me. The learning environment, as well as the simple and intuitive Python programming language, were instrumental in helping me overcome almost all of my fears.
Was there a particular moment in the Data Analyst course that was particularly challenging, but also insightful?
I experienced lightbulb moments every day during the course, because I had virtually no prior experience with the subject. The biggest challenge was certainly in the independent, hands-on tasks, where I first had to look for solutions on my own, without guidance. I especially remember a coding challenge on prime factorization with a nested for-loop, which was very new for me. This probably took me the longest to get the function to work. In the process, I experienced perhaps the biggest lightbulb moment when I finally understood what SQL stands for, what APIs are exactly, and how they work.
These are exactly the topics that others shy away from and may not have the confidence to take on. Do you have any advice to share with people who are currently hesitating?
I can imagine that most people who are interested in becoming a data analyst have a good understanding of mathematics and can handle data in Excel, but are not confident in programming. That’s a shame because they could benefit immensely from it at work. I think sometimes you have to jump in at the deep end, challenge yourself and start something new to grow personally and professionally. StackFuel has really succeeded with this entry into data science for beginners and anyone who is really interested in the topic should just dare and try it.
Apart from the learning content, how did you like the course at StackFuel?
StackFuel’s learning platform is very well designed and the use of audio-visual media, quizzes, challenges and solution checking makes programming more like a game where you really want to to beat the high score. The support team were able to help me with all my concerns and I always felt valued as a participant. I also liked the fact that in addition to hard skills, the course also teaches the necessary soft skills, such as tips for LinkedIn, XING, GitHub, portfolio work, personal blog posts and job application training. So I can really only recommend the course.
Congratulations on starting your new data analyst job just a few weeks after completing the course from StackFuel. What helped you get this job?
I came to my new job through a referral, which is why I’m starting the as a Business Data Analyst on October 1. I was very lucky. First, with my contact and second, I had the privilege of receiving a private, one-hour application training sessionwith one of StackFuel’s Educational Data Scientists upon request and because of the promising job offer. This then paid off in full in the data analytics recruiting test for the job. Of course, I practiced for days after the course until the test, because these tests are tough! But as always, that’s also just a matter of motivation.
For this new challenge, I think StackFuel has laid a good foundation for my data analytics skills using Python, Pandas, Matplotlib, and with interesting, descriptive training datasets. With any new job, you have to learn their operations and best practices and I’m confident that I’ll be able to jump right in, fresh from the Data Analyst course, and then look forward to continuing to learn on the job.
How to become a certified data analyst
Siegfried has successfully shown how it’s possible to switch careers and become a Data Analyst. With a lot of commitment and motivation, he challenged himself and proved perhaps the most important characteristic data scientists and data analysts need: enthusiasm for lifelong learning.
If you also want to know what inspired Siegfried about our learning environment, the Data Lab, then see for yourself and take a closer look at it on our website: To the Learning Environment.
Changing careers requires courage. With StackFuel, you can handle any new challenge. Find out more about our funded training courses with an education voucher from the job center or the employment agency with 100% of costs covered. Start your new data career today.