How to Start a Career in Data Science?


Data science can be a profitable career path, with sufficient opportunities to find your way up the standings. In order to get there, firstly, you have to start from the scratch. To start a Career in Data Science, you must understand the data and tools used to demonstrate the result.

Learning data science might be unapproachable especially when you are just beginning your expedition.

HBR also claims in one of its Article Data Scientist is the Sexiest job of the 21st Century.

I found some article related to the data Science, follow it to get more information related to the career in Data Science.

Here are some tips on how to start your living in data science.

Choose the right role

There are a lot of wide-ranging roles in data science industry. A data visualization professional, a machine learning expert, a data expert, data engineer is a few of the many opportunities that you could go into. Depending on your training and your work experience, getting into one role would be easier than other roles.

So, until and unless you are sure about what you want to become, you will stay tangled about the path to take and skills to refine.

career in Data ScienceTake up a Course and Complete it

Now that you have decided on a role, the next rational thing for you is to put in a keen effort to comprehend the role.

The demand for data scientists is big so thousands of courses and studies are out there to hold your hand, you can learn whatever you want to. As well as the abilities noted above, you will need credentials that prove your understanding.

A degree in mathematics, statistics, information technology, operations research, or economics would be a good preliminary. You may also want to advance into a Ph.D. in similar fields. This is not firmly essential, but will probably help when it comes to the job interviews.

List of the Courses to start a Career in Data Science

When you take up a course, go through it vigorously. Follow the coursework, projects and all the discussions happening around the course.

There is a different kind of Courses are available for each stage of learning.

  • Introductory
  • Foundation
  • Advanced
  • Domain Specific

Only doing a course end to end will give you a clearer picture of the field.

While undergoing courses and drills, you should focus on the practical applications of things you are learning.

This would help you not only understand the concept but also give you a deeper sense of how it would be applied in realism.

Choose a Tool / Language and stick to it

As declared before, it is important for you to get an end-to-end familiarity with whichever role you trail.

Choosing any of the majority tool/languages is the best to start your data science voyage. After all, tools are just means for the execution; but understanding the concept is more vital.

Language you can Choose for Data Science Career

  • R Programming
  • SAS
  • Python
  • Scala
  • Tableau
  • Julia

The idea is to start with the simplest of language or the one with which you are most familiar with. if you are not as well versed with coding, you should prefer GUI based tools for now. Then as you get a grasp on the concepts, you can get your hands on with the coding part.

Follow the right resources

To never stop learning, you have to engulf each and every source of knowledge you can find. The most useful source of this information is blogs run by most influential Data Scientists.

These Data Scientists are really active and update the followers on their findings and frequently post about the recent advancement in this field. Read about data science every day and make it a habit to be updated with the recent happenings.

Start projects

It’s important to get some experience even if you don’t have a job yet. While universities may offer projects for you to work on, those who are self-taught will need to find their own. You can go freelance and find small businesses or start-ups which need your skills on a temporary basis.

The more work you do, the more you will be able to put on your resume. If you’re having trouble, you may want to find a mentor who is already successful within the industry.

Job Search

Data engineers use more of their engineering skills, analysts are using communication and domain knowledge more, and you as a data scientist will be using mathematics and statistics.

Look on job boards to find the roles that are available and relevant to you.

If you can’t find anything in your area, consider looking further afield. Data science roles often come with hefty salaries and you may be able to justify, or even offset, the cost of relocation.

When applying to work at a company, make sure that you look into them as much as possible. Being forearmed with knowledge will really help to ace that interview, showing that you understand what is required of you even despite your lack of experience. Once you get that first entry level role, it’s all about working hard, building experience, and gaining promotions to get to those higher salaries.

The demand of data science is huge and employers are investing significant time and money in Data Scientists. So taking the right steps will lead to an exponential growth. Data science is regarded as one of the most rewarding fields of work out there at the moment, so it’s great work if you can get it.

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Pranab Mishra
Simplifying Education news and Information. Aim to reach each Individual with some Education Information. Let's Spread education together.