Try to put things you consider important for a data scientist position during your education time. If you think you did

In the bottom part of your resume is everything important to the data scientist position. You could put many variations here, but this is the one I am always looking for in the data science resume, especially if you did not have any previous employment history.

To avoid long-term wage slavery, workers who want to leave their jobs need to have options. They need to have an alternative to their current situation that doesn’t involve going hungry (or going without basic necessities). Here are a few routes I can see, based on current trends.

Many of the companies are looking for an experienced Data Scientist, but do not afraid to apply for the position if you are fresher. Sometimes, the company itself needs a fresh graduate which they could mould.

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Many ways to explain it; you could relate it to your employment history, education, or even certification. It is important to showcase this non-technical skill in a pandemic time because it is a massive extra point.

Technical skill might be self-explanatory already for a data scientist position, but it was different for the non-technical skills. It is better when you said that you have the non-technical skill; you explain why you have that skill.

Never take lightly what relevant experience you have previously; I have seen some people manage to get employment not because of their employment experience or education but because of their out-of-the-box experience they put in their resume.

While you already present the necessary technical skill at the top of the resume, you could also include any non-technical skills in this section. Let’s take a look at the example below.

This section is where you would put any relevant experience to the data scientist position, but it was not a permanent/internship. It could be an organization experience, event experience, part-time work, and anything else you deemed important for the position.

This is the classic, free-market approach to providing flexibility and freedom to workers. By growing the economy, we can create jobs and bring unemployment down. Then, when the economy is near “full employment” (categorized by unemployment around four percent), companies begin competing for workers by offering higher wages and better benefits. It is during periods of full employment that wages of lower-income earners tend to rise and quitting a crappy job becomes less risky as people have more options.

Other than necessary technical skills (Machine Learning, Programming Language, Data Analysis, Statistics), try to show non-technical skills (Communication, Teamwork, Adaptability, Quick-Thinking).

What is important is that you tailor your data scientist resume to fulfil the job application, but in the pandemic time, you need to go the extra mile to show your potential.

Every job involves doing some tasks we don’t enjoy. A job doesn’t have to be perfect all the time to be a good job. As long as there are reasons other than “my family may become homeless” that keep you coming back, it’s not wage slavery. Enjoying the camaraderie with colleagues, riding the goods and bads, or enjoying other perks, can make a job honorable and worthwhile.

We may also agree to temporarily take on jobs we dislike on our way to the next rung up the ladder. After high school, I was a busboy at a tortilla joint on nights and weekends to make extra cash. It was a miserable job that I did just for the money, but I quickly looked for something with less dishwashing and margarita lime-cutting as soon as I had something to show on my resume. But working a crappy job for a while is different from being trapped in one.

You could list down any informal course and certification you find relevant to the data scientist position, and you could also explain a little bit about what you learn during the course here.