How to Get a Job as a Data Scientist

Posted by sairaj tamse on August 22nd, 2022

Some of the most in-demand occupations today are data scientists. The field's value will only increase as data's importance in contemporary company continues to grow. Given this bright future, now is the perfect moment to pursue a career as a data scientist.

A meaningful and lucrative professional path could involve being a data scientist. These jobs are predicted by the Bureau of Labour Statistics to rise by 15% by 2029, which is substantially faster than the national average. A median wage of 2,840 was earned by data scientists in 2019.

Why you should become a data scientist may not require any further persuasion, but how to do so might be less clear. Here is a step-by-step tutorial on beginning a data science career.

Acquiring the Proper Education

Before you can work as a data scientist, you'll need the required schooling, as is the case with other occupations. A bachelor's degree in a relevant subject, such as computer science, information systems, or data analytics, is ideal. The majority of data scientists in the industry also hold a master's degree, usually in a more specialised field of data science.

You don't necessarily need to return to school for a more pertinent degree if you currently hold one. However, you have to research online courses where you might enrol in a few data science courses. Obtaining additional certificates and licences will also be beneficial.

To become a data scientist, you'll need more education than just the abilities you gain in school. Additionally, you might consider learning different programming languages and obtaining practical experience. There are several books and online courses available that can assist you in developing these skills.

Creating a Portfolio

A degree alone won't be enough to land you a job as a data scientist. Most employers will also seek out concrete examples of your abilities. Former Apple senior data scientist Mohammad Shokoohi-Yekta advises that practical experience and comfort with code are more important than theoretical knowledge.

The most effective way to demonstrate your familiarity and expertise in this field is through a portfolio of your work. Start participating in practical data science initiatives as soon as you can and gather them into a portfolio. This can be accomplished through side projects in your areas of interest and freelance data work.

To demonstrate your adaptability, your portfolio should contain a wide range of diverse data science projects. You should exhibit expertise across a range of programming languages, sectors, and project kinds. Your participation in any data science-related competitions will be a great addition to your portfolio.

Obtaining Employment

You should begin looking for a job once you have a relevant education and a sizable portfolio.

Although adaptability is always useful, you'll probably succeed more if you focus on a particular industry and have a set of credentials and certifications. For instance, CMMC compliance is a requirement for all Department of Defense contractors, thus obtaining this certification could increase your chances of landing a job with the DoD.

Don't forget to personalise your CV and cover letter for each opportunity. Emphasize your qualifications that are most pertinent to the business and job at hand. Increase your network on LinkedIn, apply for jobs through websites like Indeed, and endeavour to establish a credible online presence so that companies will take note of you.

It's okay if you initially are unable to secure a career as a data scientist. In fact, it could be wiser to start by applying to relevant but entry-level jobs like data analysis. From there, you can advance your career.

How to Advance Your Career

The finest resource for enhancing your career is on-the-job experience. Try not to be overly picky about the first job you accept in light of that. Even if a stable employment in an area involving data isn't what you're looking for, you might still want to accept the offer. Consider your first position in data as a launching place.

For your first employment in data science, the optimum company size is one with 50 to 500 workers. You will have many opportunities to advance and have access to senior data scientists at these medium-sized companies. Take the initiative once you begin working at your first job by attempting to complete as many projects as you can without being overburdened.

You'll acquire more pertinent experience the more you look for fresh chances within your organisation. As you work, look for opportunities to advance, both within and outside of your current company. You will quickly advance in the field of data science if you exhibit initiative and a superb work ethic.

Start your career in data science now.

It's never too late to begin a data science profession. Don't put it off, though, if you know it's what you want to do. You may start acquiring the knowledge and experience you require right away. Although being a data scientist is not simple, if you follow these guidelines, you can have a successful and lengthy career in the field.

Would you like to learn more about the data science industry and possibly become one? Take up Learnbay’s data science course in Bangalore and get chance to work on projects with professionals in the field.