Data science is the “sexiest job of the 21st century” and might also have the highest paycheck compared to a lot of other jobs. And despite these perks and benefits, there is a burning question that often puts people in a serious dilemma — is data science the right fit for me?
There are people who end up becoming a part of this tribe and then later regret when things turn difficult. This is mostly because of the hype that gets created at a certain point of time and when we see everyone following data science.
In this article, we are going to list some points that would help you figure out whether data science is a good fit for you.
How Well Do You Understand The Data Science Domain?
This is definitely the first and foremost question you must ask yourself when you are considering data science as a career. Data science is a really vast domain and requires deep knowledge and specific skill set to excel.
Further, it’s not just the knowledge and skills, but you also have to understand the different job roles in this industry and the difference between them. For example, the role of a data scientist is different than the role of a data engineer. Once you look at all the different job roles, you would get an idea about what the work is and whether you fit any of them.
Some of the job roles are:
Data Scientist
Business Analyst
Data Analyst
Data Engineer/Data Architect
Statistician etc.
How Well Do You Gel With Mathematics And Statistics?
Mathematics and Statistics are two of the most vital pillars of data science. They are so important that their concepts are extensively used in the data science field. So, lately, if you have been wondering about starting a career in data science you have to assure that your knowledge and skills with mathematics and statistics are top-grade.
Cement this fact in your mind that you will have to work with numbers extensively if you are working as a data science professional. You will have to spend a significant amount of time to build a great bond with numbers. You will also need to figure out what are all the prime concepts that will be used in your day to day data science job.
To give you an idea, here are a number of statistical principles and theorems that matters a lot when you are trying to enter the data science domain:
Linear Algebra
Dimensionality Reduction
Probability Distribution
Central Limit Theorem
Bayes Theorem
How Well Can You Analyse Things And Solve Problems?
While data science is definitely about algorithms and models, there is something that you cannot ignore when you are working in this field — analysing and solving problems. For instance, when you are playing games like chess or card, what approach do you take? You play completely depending on your luck or you analyse the entire scenario and then make your next move? Luck contributes a small percentage, but your strategies matter a lot.
It is same with business; you will have to think based on both rational and emotional aspect. You will have to have the mindset of finding a solution to the complex problems and challenges businesses face.
How Much Time You Can Devote To Learning?
As mentioned earlier, data science is a vast domain and the learning process takes time. It’s not just the concepts, but one needs to have a 360 degree understanding of the entire domain which includes the tools and methods as well.
If you are working professional who is occupied much of the time with office work and the family and doesn’t have much time to put in for learning, then you might have to figure out a way to manage. You can take up online courses or even make use of free resources. Enrol yourself to some data science course, engage with the community, work on projects and once you are ready enough, make that move to land a job.
Do You Love Working With People/Teams From Different Department?
Being a data scientist in an organisation doesn’t mean you would work the entire day with people from your domain. The prime reason why a data science department is there in an organisation is to solve different problems and these problems may come from a different domain.
This scenario also includes things like communication and presentation skills. As a data science professional, you would also have to present your work, findings, and results to a set of people. You will have to be creative and good storyteller when you are interacting.
Here are some of the most vital skills that you need to be a data storyteller:
1. Ability to understand the target audience
2. Should be able to discover the sole purpose of the data story
3. Should know how to make the best presentation
4. Skills and knowledge of data visualisation tools
So you have to make sure that you are comfortable spending a significantly large proportion of your time with people doesn’t understand or do data. Ask yourself whether you would be able to interact with such people and make them understand what you are working on and how you are solving these problems.
Krish Charlie... 🖋
Comments