Is Your Data Science Career Dying?

Data science lives in the heart of the industry. It is making the world better with its services. If you hunt the internet for the most lucrative job opportunities at present, then you would find data science at the top.

Data science is furnishing its services in all sectors of the industry. Whether be it healthcare, education, business or anything else. Apart from its applications, it is a bright career option as well. As the facts revealed, there are high vacancies for data scientists in the future.

As we can see from the graph, the data scientist is the most demanded job profile at present. But do you have a dilemma about your career in data science? Do you feel that your career isn’t safe with data science? Maybe you do so because we believe what we see.

‘Coz you closer to your Data Science Dream

Many people think that “Career with data science isn’t safe”. Though, “data science is one of the most lucrative jobs” has been trending on the internet. But we cannot assume and plan our career according to something which is trending on the internet. Let’s have a look at the reasons why data scientists are leaving their jobs or why are they losing their jobs.

REASONS WHY DATA SCIENTISTS ARE LEAVING THEIR JOBS

Reality is different from expectations:

This is the biggest issue a data scientist face in a company. Data scientists didn’t get what they expect from the company. On the other hand, companies also feel the same. This brings a huge gap between the company and a data scientist.

A data scientist thinks that he is supposed to write cool machine learning algorithms for solving complex problems but before doing this they need to create analytical reports or sort out the data infrastructure. This is so because many companies fail to hire senior or experienced data scientists.

Along with this, companies do not provide the infrastructure which is required for carrying out insights using AI. Data scientists don’t get to work on things in which they are interested which makes them unhappy with their job roles.

Politics reign supreme:

Do you think, Machine Learning Algorithms will make you the most valuable employee for a company? Though, this is one of the problems faced by the data scientists. Data scientists expect that machine learning algorithms are gonna make them valuable, but this is not true.

Do you know what is Machine Learning?

Data scientists need to work on things they haven’t expected. They need to work on getting numbers from the database for delivering it to the right people. Such things are really irritating for a skilled data scientist.

People make misconceptions about you:

Many people don’t know what exactly a data scientist is and what tasks a data scientist is supposed to do. A data scientist is supposed to be an analytical expert as well as a database master. However, non-technical executives are not the only people who make too many assumptions about a data scientist, technical persons also do the same.

They think that a data scientist is well familiar with all the things relevant to the data which includes frameworks, tools, etc. On the other hand, if we talk about the job specifications, if you see such relevant job specifications for a job profile, then be aware.

This is so because there are many companies that don’t even have a data-driven strategy and are looking for data scientists.

HOW TO SAVE YOUR DATA SCIENCE CAREER

Apart from all this, data science is still a better career option. Let’s dig out how one can save their data science career from dying.

SKILLS:

For being a successful data scientist, you must possess all the skills which are required by the companies in a data scientist. Let’s go through the technical and non-technical skills which a data scientist must-have.

Technical skills:

Mathematics, statistics, probability → A data scientist must have good command over math, statistics, and probability. As a data scientist have to deal with the analysis of the data.

• Python → Python is essential for getting into the world of data science. Python comes with an ample amount of libraries that are vital in data science.
• R → R is another widely used language in data science. R deals with the visualization of the data.
• SQL → SQL is also a very important skill that a data scientist must-have. A data scientist needs to collect the data from databases for which SQL is required.
• Analytical tools → Data science deals with different types of analysis and for that, it works on different analytical tools. A data scientist must know how to work on these analytical tools.

Non-technical skills

• Communication skills → A data scientist should have excellent communication skills. Being a data scientist, you need to deal with the clients of the company. You need to understand their requirements properly such that you can give them the desired results.
• Business acumen → A data scientist should have good business acumen. As a data scientist, you must know how to deal with risky business situations.
• Data intuition → A data scientist is known for playing with the data. By looking at the data, you must recognize what information you can extract from it. A data scientist should have the power of understanding the data.

PROJECTS:

Though, projects are the most valuable investment that anyone can make in learning data science. Projects give you exposure to real-world problems and thus will boost your practical insights. A data scientist is supposed to have much better practical insights than anyone else.

By working on projects you’ll learn many new things which you didn’t get to learn in theory. Moreover, projects will add stars to your resume. That’s why projects are a must if you are an aspiring data scientist.

INTERVIEW QUESTIONS:

Data science interviews are not much easier to deal with. Along with technical skills, soft skills are also required. Data science interviews are not the same as the other interviews. Maybe the interviewer gives you a problem to solve on the spot. You need to prove yourself and your skills to the interviewer. So, prepare yourself by practicing different interview questions and crack the interview.

BOTTOM LINE:

So these were the problems which are faced by the data scientists. Unquestionably, data science is exploding in the industry. Somehow, you can save your data science career by enhancing your skills. So what are you waiting for then? Get up and do backbreaking practice to polish your skills and become a skilled data scientist.

Demand for data scientists is touching the sky. So, get ready to make the world better with your amusing data science skills.