Data Science is the coolest player in our era. Companies in various industries realize the potential of creating value with data. The value can be in any form such as improving a production process, better predicting demand, more accurate sales forecasts, and so on.
Such a popular field with numerous job opportunities attract people. Not only students but also people who already have a professional career decide to work in data science field.
I’m one of those who decided to make a career change to become a data scientist. It took me two years to land a job in the field. It was a journey with a mixture of feelings. I really like this field so my journey was exciting and fun in general. I sometimes felt exhausted but never lost my motivation.
After landing a job as a data scientist, I realized what a right decision I made. The long nights and weekends paid off. It was nights and weekends for me because I had to keep my other job while studying data science.
I would like to share 3 things that I think will motivate aspiring data scientists.
Real life data
The most important part of our job is data. Without proper data, we are only able to scratch the surface. The available data for studying and practicing is usually not real life data.
The ready-to-use datasets are almost always neat and clean. They are not challenging enough. You can the learn the basics with such datasets which might become a little boring after a while.
Such datasets are helpful for practicing and learning the basics. However, the real life data is messy and much more complicated. It requires a lot of work to clean, process, and infer meaningful insights.
Once you start working as a data scientist, you will have the chance to work with real life data. It is much more fun and exciting. You will feel like you are getting proper work done.
Another advantage of working with real life data is that you will have the chance to infer meaningful results. Depending on the field you are working, you might be surprised with what the data tells or shows you.
Collaborative environment
I have followed a self-taught process to learn data science. Although there are various resources available to learn and ask questions, having a data scientist colleague or colleagues is a highly valuable asset.
You have the chance to discuss your ideas and do brainstorming. You will discover different ways of accomplishing a task. You will gain knowledge and improve your skills much more quicker than before.
What a collaborative working environment offers is more valuable than the best MOOC courses or online certificates. Being able to discuss your solution or implementation makes it more fun.
It will not always be you learning from your colleagues. In some cases, you will provide a better solution or be able to help a colleagues. Such circumstances will boost your motivation.
Production level data science
The data science learning journey is likely to be bounded by jupyter notebooks. We download a dataset from the web and practice in a notebook. Typical tasks include cleaning, preprocessing, analyzing, and visualizing the data.
This workflow is fine for learning and practicing. However, the feeling of working at production level can never be achieved with jupyter notebooks. The feeling when you see your solution is deployed and used in production for the first time is priceless.
To work in a production environment with real life data is something we cannot achieve with certificates, courses, or tutorials. It may be challenging at first but will further motivate and excite you.
On the down side, making a mistake in a production environment is costly. You will have to be extra careful. However, mistakes do happen. Instead of letting such mistakes demotivate you, consider them as opportunities to learn new stuff and improve your skills.
Working at production level requires to collaborate with other professions such as software engineers. In some companies, you will need to extent your scope and do software related tasks as well. I see this as an opportunity to acquire new skills.
Conclusion
Although data science is such a popular and in demand field, finding your first job might be harder than you anticipate. There is a lot to learn and it is not easy to showcase what you know without prior job experience.
However, you will eventually get that first job if you keep studying. I wanted to share my experience that I think will further motivate you to reach your goal.
I’m more than glad that I decided to make a career change to become a data scientist. My motivation and enthusiasm have increased since I started working as a data scientist.
Thank you for reading. Please let me know if you have any feedback.