Tips on Boosting your Data Science Career

Everything is getting digital, and this implies that data science is here to stay. In fact, the value of data science and data analytics is going to proliferate in the upcoming years. A distinct benefit of data science as a career option is that there’s a significant amount of education available through online sources. You can go for Data Science courses which are available for students and professionals to upskill their career. Till then, let’s take a look at these simple tips to get a good head start in your data science career.

1. Pick the Right Role

There are several roles in data science such as machine learning, data visualisation, data engineering etc. For instance, if you are a software developer, it wouldn’t be difficult for you to shift into data engineering. Based on your education and your work experience, you can select the role that best suits your skills and interest. Therefore, unless you are precise about what you want to become, you will stay doubtful about the skills to hone and the path to take.

An important point to keep in mind while selecting a job role: don’t just thoughtlessly jump on to a position. You must understand precisely what the field demands and prepare for it accordingly.

2. Take up a Course

Now that you know which role you want to pursue, the next logical thing for you is to do is put in efforts to understand the role. The need for data scientists is big; hence there are many courses available wherein you can learn whatever you desire. You can join an accreditation program which will take you through all the requirements that the role requires. The main purpose should be whether the program teaches you the basics and guides you to a suitable level, from which you can advance further. For example, if you take up a course on big data, you would get a thorough understanding of the data structure and how you can manage it to deliver meaningful insights.

3. Pick a Language/Tool

It is important to get an end-to-end practice of whichever language (Python, R, etc) you proceed with. Choose any of the mainstream languages/tools and begin your data science journey. Tools are just a way for implementation, but understanding the concept is more valuable. There are several discussions/guides available on the internet which discuss a particular topic. It is best to start with the easiest of language or the one with which you are most comfortable. For instance, if you are not as well versed in coding, you should go for GUI (graphical user interface) based tools, and then as you get a grip on the theories, you can direct your focus on the coding part.

4. Join a Peer Group

The next important step for you to take up is to join a peer group. This is important because a peer group helps you stay motivated. Pursuing a new field may seem a bit daunting when you do it solo, but if you have acquaintances/friends with you, the task appears a bit easier. The preferred way to be in a peer group is to have a group of people you can physically communicate with. You can also interact with people over the internet who share similar goals. Even if you do not have a peer group to go to, you can still have a significant technical discussion on the internet. There are online panels and forums which give you this kind of setting such as StackExchange and Reddit.

5. Concentrate on Practical Applications and not just Theory

While going for training and courses, you must also focus on the practical applications of concepts you are learning. It would help you not only learn the theory well but also give you a deeper understanding of how it would be implemented in reality.

A few tips to undertake when following a course are as follows:

• Make sure you do all the assignments and exercises to understand the applications.
• Work on an open data sets and apply your learning. Even if you don’t get the maths behind a method initially, note the hypotheses, what it effects and how to evaluates the results. You can always acquire a deeper knowledge at a later stage.
• Have a look at the answers by people who have worked in the field, as they would be able to help you with the accurate approach.

6. Follow the Right Resources

To keep the knowledge pond full, you have to immerse yourself in every bit of information you can find. The most effective source of information is blogs/sites run by prominent Data Scientists. Certain Data Scientists are active and update their followers on their findings and generally post regarding the current progress in the field. It is best to read about data science every day and make it a practice to stay updated. But make sure you don’t follow the incorrect studies and applications.

Here is a list of Data Scientists and important newsletters that you can follow.

1. WildML
2. NYU
3. KDnuggets News

7. Networking

Firstly, your undivided attention should be on gaining knowledge. Once you have got a hang of the domain, you can go on to attend industry conferences and events or participate in hackathons. In a public meetup, you get to interact with people who work actively in your field. This gives you networking opportunities along with building a relationship with them, which, in turn, will help you develop in your career. A networking contact can mentor you or help you search for a job.

The requirement for data science is huge, and organizations are investing significant time and money in Data Science. Therefore, taking the right steps will lead to exponential growth. The tips mentioned above can help get you started and dodge some common errors.

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