Why it feels IMPOSSIBLE to get a data analyst job | AI, career, tech

Why does it feel impossible to get a data analyst job? They say data is the new oil of the digital economy and unemployment rates are at its lowest. Then why is it still so hard to get a job? I'll discuss three reasons why and what you can do about it. The first is fear-mongering from the media. Starting in 2022 with the concerns of an economic recession, the tech companies started massively laying off their employees. This includes fang companies and in the last few years, over 450,000 people have been laid off. And if you've seen the media posts left and right, tech jobs are over, another wave of tech layoffs, it makes it seem like the tech economy is doing horribly. But is it really that bad? And is it that bad in particular for data analysts? Well, let's look into the data and dig a little deeper. Who is impacted by these layoffs? 365 Data Science did a recent data analysis on who was impacted by the recent tech layoffs and the findings were really interesting. Of the recent layoffs that happened, 27% were from HR, 22% from software engineers. And if you dig into the data a little deeper and look into the companies, you'll see that data analysts and data scientists make up less than 5% of the overall tech layoffs. So what does this mean? It means yes, tech layoffs are happening, but the jobs that are mostly impacted within tech are HR and recruitment-related job titles. This means that data analysts and data-related jobs are less impacted by the overall tech layoffs. But by looking at the Reddit threads and the news and media outlets, it seems like data analyst jobs are dead and over and you shouldn't even start learning these skills because it's a dead-end role. What else do we know about the profile of someone who's been impacted by these tech layoffs? 365 Data Science did the analysis and said that the average profile of someone who's been impacted has been with the company for about two and a half years and has an overall work experience of around 12 years. This makes sense because when companies are tightening their budgets, the easiest way to get rid of their costs is by getting rid of labor. And if you look at the profile, two and a half years means that the person was most likely hired during the pandemic. So tech companies overhired during the Great Resignation. And the 11 to 12 year range shows that the person was most likely probably overpaid. And when you compare the salary of someone with 12 years experience versus a junior with one year experience, clearly you can save more money by getting rid of someone who has more experience. So what is the impact of these layoffs? This brings me to my second point, which is more competition in the job market. Although 5% is not a large percentage of the total tech layoffs, 5% of 450,000 is still a lot of people. And based off the profile, this person is most likely someone who has lots of experience. And now they're entering the job market and competing against the same jobs as someone who is just learning the data analysis skills and entering in the data market now. At the same time, you can see that the hiring for tech has really decreased since 2022. So you have more people in the market looking for tech jobs, while there's significantly less roles available. But it's worth noting that not all industries are suffering. The US economy added 353,000 jobs in January, which is two times more than economists expected. Tech is just a small industry of the broader economy, and there are data roles continuously being added outside of tech. So this tells me that if you're someone just entering the job market and looking for your first data analyst role, don't look at just tech. Look at other industries because it will be a lot less competitive, and you'll have more opportunities by expanding your search outside of just that one sector. Another point to consider is, is AI and automation impacting the job market? According to 365 Science, the fact that 27% of the layoffs were HR and recruitment shows that this may be a sign that those roles can be automated and the impact of AI is already starting. And the new trend within tech now is to do more with less, as in squeeze more work out of less people. In a recent earnings call, Amazon CFO said, we're going to continue to be careful on what we invest in, and we're going to continue to invest in new things and new areas and things that resonate with customers. And where we can find efficiencies and do more with less, we're going to do that as well. And this is how American capitalism works. As companies are pressured to increase their bottom line, companies now have to think about how to do more with less. And that's where you can see signs of AI and automation because automation allows you to do more with less, and this is starting to impact the job market. So what can you do to stand out? As the job market changes and AI is shaking up the industry, you have to continue to upskill and stay adaptable. LinkedIn just released their top 2024 in-demand skills, and the top skill listed in there is adaptability. As you can see, the pace of the world is rapidly changing, and the people who are thinking, oh, it's impossible to get a job, why even start, are the ones who are left behind while the other people who stay adaptable are figuring out how to get new skills, furthering their career, and they're the ones who will get hired as the world changes. And yes, it is harder to get a job now than it was three years ago, but it doesn't mean that it's impossible. It just means you have to do things differently. You can learn the top skills on this list and include them in your resume to make yourself stand out. And I'll link my video here on how to write a data analyst resume so that you can use that as a reference. And other key skills that stood out for me on the list are communication, analytics, and problem solving. These are key data analyst skills, and learning these skills will not only make you stand out as a data analyst, but also give you opportunities for other career paths as well. From my experience, the project managers or consultants who know how to pull their own data and not have to wait for the data analysts are the ones who do succeed. As companies start to use more data and AI, having data analysis skills will be so much more important. And even if you realize that you don't wanna become a data analyst or you're unsure whether the data analyst field is for you, just having these data skills will be so fundamental and allow you to really stand out in your career for 2024 and beyond. I will continue to create more videos on how to do data analysis, so please subscribe and like this channel. And if you wanna learn how to think like a data analyst, I will link this video here so that you can get started. And thank you so much. I will see you there.