Data Analyst Resume Rejected? I'll show you a portfolio that actually works

Is the 'Data Analyst' career just an illusion for non-majors, humanities graduates, and academy completers? 🤔

I entered the data analyst job market at age 31 and got hired, so it's not an illusion!

When I suddenly said I was going to quit my office job to become a data analyst, everyone around me said the same thing.

💭"Changing careers after thirty? It's tough, especially at your age."

💭"They say you can't get a job unless you have a master's degree. It'll be hard to even pass the initial screening."

But I just did it anyway. Because,

"Oh, because I want to be a data analyst!"

<But here is my job hunt failure story>

I boldly declared my goal and applied to nearly 40 places, but news of passing the resume screening? Only two spots. (And even those were a bit strange...)

(These are just the records from Wanted... My applications on other platforms before May were also a parade of document rejections.. ^^ Wow.. really..)

saying I would become a data analyst

I told my parents and let all my acquaintances and friends know, but including the academy course period (6 months) and the period of constant document rejections (3 months), I spent quite a long time as a gloomy, unemployed person. 😥

At that time, I would walk around the neighborhood to try and get rid of the depression, but around quitting time, my friends' group chat would be filled with talk about their companies and work...

And when I came back to my room, I'd think, 'What am I even doing..?' and feel depressed all over again. It was a repeating pattern. (I even got stress-induced gastritis back then.. haha😂)

After completing the academy, every single day was depressing during the period when I couldn't even pass the initial document screening.

"What on earth is the problem.."

After spending 2-3 months in this state,

I had a strong feeling that the reason things weren't working out to this extent wasn't just because of my specs.

'I'm a non-major and an academy graduate, but if you hire me, I can definitely do "this much"'—maybe that's what's missing from my portfolio. My portfolio is the only thing I have to show...😯

It was because I kept having these thoughts.

Anyway, I knew I had to revise my portfolio, but I just couldn't get a feel for how to do it.

But I couldn't just stop there,

I kept looking through well-made data analysis materials on overseas sites,

I started getting hints by looking at the patterns in their analytical writing.

As soon as I realized it, I applied it to my portfolio immediately.

Once I felt confident in my portfolio, I applied to about 10 places I wanted to go, and more than 90% of them sent me news that I had passed the document screening.

<After Portfolio Changes>

✅<So, the story of my successful job hunt>

The reason I, someone with no impressive credentials to speak of, was able to successfully transition into a technical IT role in the STEM field as a data analyst is that I deeply realized the importance of a "portfolio."

At first, I was dazed by the continuous stream of notifications that I had passed the document screening, but

Later, as I looked at the portfolios of new applicants at our company and provided portfolio consulting for aspiring non-major data analysts from the outside, I became increasingly convinced that the method I realized was correct.

The reason why I had virtually zero document screening passes for 2-3 months

I have come to my own conclusion that it was because "I presented a portfolio that was impossible to evaluate."

I, too, just like everyone else,

Even though I submitted my portfolio structured as Data Analysis Goals -> Preprocessing -> Visualization -> Machine Learning Modeling -> Conclusion, I failed every single application.

The structure of the portfolios that passed and those that failed were similar, but the problem lay in a completely different place.

There is a clear distinction between a portfolio that can be evaluated and one that cannot be evaluated.

So, I am sharing these tips with you.

First. Portfolios that can be evaluated

Second. A highly rated portfolio

This course is more tailored toward job seekers who are non-majors.

This course is not difficult at all.😎

This is not a lecture about how to do machine learning more brilliantly or how to increase accuracy.

Therefore, anyone preparing for a job as a data analyst can take this course.

Additionally, I will even provide tips on how to handle interviews after passing the document screening!

The reason I am posting this lecture at this price is,

I have been running a free portfolio consulting post for aspiring data analysts for 3-4 years, and many of them sent me coffee gift icons as a token of gratitude after getting hired. So, the price is roughly around that amount... (considering the commission paid to Inflearn...() )

Recommended for these people

After taking the course,

• You can find out what kind of portfolio hiring managers are looking for.

• No matter how poorly it is made, you will at least learn what a portfolio that is "worthy of evaluation" looks like.

• As a non-major, you can learn how to respond to questions you might receive during an interview.