Required Qualification for Data Science Entry-level Jobs

Given that the data science industry has grown rapidly over the last decade, it comes as no surprise that it has turned out to be a lucrative career path. However, you need to start somewhere to get on a data science career path. In most cases, a data science career begins with an entry-level job in the industry. There are requirements for education, skills, and experience for these jobs. You should have a cohesive plan and take the necessary steps to begin your journey in data science. 

Educational requirements for getting an entry-level data science job

If you are an aspiring data scientist looking for an entry-level job, you need to have a specific educational qualification. You have a better chance of finding success in the field if you have a postgraduate degree from any of the quantitative fields. Most data scientists have a major in computer science, so it is an advantage in the field. 

Is there any experience required for entry-level jobs?

Apart from relevant education, some form of experience credentials is also required in the data science field. Approximately 35% of individuals working in data science have already had jobs in similar positions. What this means is that the rest 65% of data scientists previously had a different occupation. So, around 2 out of 3 data scientists are working on their first job in the field. 

So, you can assume that getting an entry-level job in data science is very much achievable. Having said that, you cannot expect to land a job in the field straight after school. Very few data scientists start in the field before working in a previous position. So, even if you are merely aiming to get an entry-level job in data science, you still need to have some experience previously. This goes to show that the position of a data scientist is quite demanding nowadays. While it is hard to get and demanding, it is certainly not impossible. 

What are the recruiters looking for?

Recruiters and employers are always looking for data science professionals who have a mastery of data, the necessary tools, and the business side of things. Simplilearn’s Data Science Program is an excellent place to get started on all these things. 

When it comes to data science tools, you are expected to be comfortable working with the most used software on the market. You should at least know Python or R, or even better – both. Other tools that are very important for a data science professional include visualization software such as Tableaus and Power BI and SQL. MS Excel remains to be one of the prerequisites for any data science job description. 

The job of a data scientist is to know where the data is coming from and the best ways of pre-processing and processing the data. Most significantly, you need to be able to gain actionable insights from the data. 

Before applying for any entry-level data science job in a company, you should get to know about:

• The skills required for landing a job in the position
• The aspects of data science that the business utilizes

It is always advantageous to have market expertise in a particular field. So, you are better suited for an entry-level job in data science if you have a more holistic understanding of the industry and the data. 

What skills do you need?

In general, for most data science roles, you are required to have good skills in coding, analytics, and statistics. If you do not have mastery of all three of these skills, you are not alone. You do not necessarily have to excel in all these fields to land an entry-level data scientist job. You do need to be good at programming and if you have one of the other two skills, you should be good to go. 

 You should know that employers look to hire candidates with skills that are transferable and can provide value to the company. Some of the transferable skills they look for include the ability to take initiative, set demanding goals and doing what’s necessary to exceed those goals. Interpersonal skills also easily translate across different contexts and industries, so you should have it covered as well. Other skills that employers appreciate include:

• Ability to make positive changes
• Learning from experience
• Self-direction
• Accountability
• Independence

A great way to show your potential employers that you have these skills is to include internships or projects in your resume. It shows that you can work on projects with a team and you are proficient in coding. 

Networking is important as well

Data science is a competitive field and networking can be as important as your skills. This is particularly true for aspiring professionals trying to get started in the field. So, you should be prepared to do whatever’s necessary to get hold of someone who wants to give you a chance, even for an entry-level position. You can boost your chances of getting hired by getting referrals from the company’s employees or a recommendation from your previous employer. 

Landing the job

You might have to go through multiple rounds of tests and interviews to eventually land a job. Potential employers may take a written exam for testing your statistical skills. Similarly, they can provide a remote task to check your programming skills. Your communication skills are only showcased during your face-to-face interview. So, it is up to you to highlight how coherent you are with communication. 

To sum it up, the steps to get an entry-level data science job are:

• Earn a relevant degree with a quantitative major, preferably in Computer Science
• Gain some experience in a field related to data science. IT professional or analyst jobs are great to get started with
• Improve your coding skills and learn how to work with data. Knowledge of the line of work is essential as well
• Additionally, try highlighting some important transferable skills in your resume
• Engage in networking and see if you can get referrals or recommendations for entry-level positions. 
• Showcase your soft skills like curiosity and communication during the interview.