It is exciting to choose a different career path and often accompanied by a lot of thoughts and doubts. 21% of people looking for a new job do so out of interest in a different field. Why? I jumped into the deep end myself to become an analytical engineer, so this blog is all about the inside perspective.
Why changing careers?
There could be many reasons to change careers. Amongst them are to follow a passion or to find new experiences. It’s difficult to find data about career changes, simply because the term “career change” is quite ambiguous. However, the change from human movement scientist to analytical engineer seems like a career change to me.
Passion for data
A human movement scientist in the academic field does a lot of research. This can be both as literature studies or practical studies. The results from practical studies often include several variables with different units. Hence, in order to analyze the data it is important to structure and transform the data. Unfortunately, the datasets from research are often rather small. This limited my skill development in structuring, transforming, and analyzing data, but did initiate my passion for it.
From sports to IT: creating a new experience
Information technology becomes increasingly important in sports. In cycling, information technology can be used to optimize training plans, improve aerodynamics, and to predict functional overtraining. It can also be implemented to make the whole team operate more efficiently. When I worked as an exercise physiologist I learned that cycling teams and sports companies are not yet mature when it comes to data implementation. Mostly because they don’t have departments that can ingest and transform data to use for analytical purposes. Hence, I wanted a new experience to learn to prepare and transform data for analytical purposes.
Analytical Engineer at Nimbus Intelligence
In the search for a new experience I quickly learned about Nimbus Intelligence and the program to become an analytical engineer. An analytical engineer uses tools such as Snowflake, SQL, Python, and dbt, to transform, test, deploy and document data. I had some experience with programming languages, but it was still a jump in the deep end to become an analytical engineer. Now, two weeks into the program, I can confidently say that I do not regret that I followed my passion for data and the urge for a new experience.
