“{Your major} Fresh Graduate with a passion for {the business you apply} and data science. I am experienced in analyzing

I would show you what my example for an experienced data scientist employment history looks like. We show our employment history first, with the latest employment at the top.

For your consideration, keep tailor the description suit to the company business. Don’t just blast the same resume to every single company. The HR know which resume is specifically made and which one re-send to many.

You could also include any internships here for you who did not have any employment history. If you only have volunteering or organizational experience, you need to put your education section first.

During the pandemic time, with social distancing and work-from-home situations, you would need to rely on your communication skill and quick thinking whenever problems arise. This is why it is important to showcase your adaptability, communication, and quick-thinking skill in your description.

a. I have mentioned previously that communication and adaptability are important in pandemic time. Point a is an example of how you could show your communication and adaptability skills in employment.

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ges are R and Python. It is important to point out that they are not mutually exclusive. R is more suitable for statistical analysis while Python is more appropriate for machine learning. This doesn’t mean that you cannot do machine learning with R or statistical analysis with Python. Personally, I mostly work with Python but it sometimes happens that we deploy packages written in R. It depends on the industry and your (future) company production environment’s standard. My recommendation is to learn both of them!

Above is an example of my education history. It would be best if you put your recent education on the top and going backward from there. Actually, I did not come from a computer science or math/statistic background but could still secure a data scientist position. This means that the Data Scientist position is not reserved only for people from computer science and/or math/statistic majors.

I never recommend anybody to use the percentage or bar to show how capable you are with each skill because it looks unprofessional. It is better to say you are proficient, capable, expert, or any other word explaining your skill capability.

That is the example if you do not have any data scientist experience. Try to over-sell your employment experience as that is the point of having your resume, but do not lie in your resume. It is fine to glorify what you have done in your resume because you could explain what you do, but lying in your resume would only backfire to you in the end.

In your skill section, you could outline your capability in each of your skills and showcase your data science portfolio example. For me, I often put the link to my project in this section.

Fresh Graduate and Non-experience person description at the very least need to showcase your interest and potential as a Data Scientist. Although, there is an extra point you need to add during this pandemic time

That is the above example if you have experience as a Data Scientist, but what if you don’t have one? You need to explain what you do in your previous employment/internship as close to why you are a good potential as a data scientist in the company you are applying to.

Above is an example employment section for an experienced data scientist. In this section, I outline four bullet points important for the Data Scientist position, especially in pandemic time. The points are:

This section is often glossed by HR, but when the HR already takes notice of your resume, they would certainly read this section in much deeper. Let’s take a look at what kind of experience we should put in our data science resume.

The next section after your employment history should be your education. This section often short and concise, but depending on your employment history, you could explain more what you did during your learning time.