I Studied Data Job Trends for 24 Hours to Save Your Career! (ft Datalore)

Where is this data from? Like is a specific country?

I have been a data scientist for ten years, but unemployed and having very few opportunities for 5 months already.

I'm currently in a career shift moving from general supply chain, to data science. I really appreciated this video, and it's a great reminder of how much there is to learn haha

1- Job Market Stability: Despite a 15% decrease in data job postings since 2022, the demand for data roles like data scientists, analysts, and engineers has remained stable, even amidst tech layoffs. However, the market has become more competitive, with companies prioritizing efficiency and cost-cutting.

2-Technical Skill Consolidation: Python has emerged as the dominant programming language, with 86% of data scientists using it for projects. SQL remains equally important, appearing in about 60% of job postings. The video emphasizes learning both Python and SQL for anyone entering the field.

3-Rise of AI Engineers: A new role, AI engineers, is growing rapidly due to the development of large language models (LLMs). Unlike machine learning engineers, AI engineers focus on using pre-trained models to solve business problems. This role does not typically require a PhD, but it does demand expertise in prompt engineering and AI workflow design.

4-Growth of Freelancing: There’s a growing demand for freelance and contract data work. Freelancing offers flexibility and a diverse range of projects, which is great for skill development. Finding freelance work can start with personal networks and platforms like Upwork and Fiverr.

5-Impact of Low-Code/No-Code Tools: The rise of AI-powered low-code and no-code tools is making data analysis more accessible to non-technical professionals. These tools automate basic tasks, potentially reducing entry-level data job opportunities but opening up roles for those with domain expertise and minimal coding skills.

I personally think data management and data governance professionals will be in very high demand in the years to come, with most medium sized companies trying to go AI native.

Data strategy is becoming increasingly necessary.
Especially with growing concerns about data privacy, protection, and just the extra large volumes.
After i saw what happened with MTN in Nigeria some years back, i realised how big of a deal data governance is going to be, now that AI is involved.

Bye bye white collar jobs, period.

I feel like being good at what you do is one of the most important things because people often say they can do something but usually they can barely do it as oppose to being excellent at it.

python being chosen as the main language is prooof that eventually coding will be just natural language

Great video with alot of great insights! Thank you!

There is ONE thing that everybody who wants to get into the field should know… IS NOT FOR EVERYBODY. You need to be willing to put long hours, great at dealing with lots of math and being quick at thinking/implementing solutions. If you don't have them, one or more of these three scenarious are going to happen: either you won't know whatever is you are doing 50% of the time, or you won't know how to explain things prompting people to wonder wth is that you do, or worst, your incompetency will be revealed sooner or later by others who have these 3.

12:09 List of job titles in data

Hello Thu, the video gave me some motivation and hope thanks to the idea of becoming an AI Engineer. But why would an AI Engineer need to know stats, differential equations, advanced deep learning , and advanced Python and advanced SQL (as suggested at 8:00) if they will be using pre-trained models and pre-built tools? I can see why one would need to know the basics. I'm particularly curious to know why the Calculus and Linear Algebra are necessary, as the math is the main reason why I want to get into Data Science.

Offshore freelancing is a big thing too, companies can find good analysts by a quarter of the US salaries

Hey Thu Vu! Do you edit videos yourself or have you hired someone? I’m an editor and would love to discuss it if you’re interested

just discovered you, and your explanation is wow. I have already watched a few of your videos 🙂

Fully agree with SQL as indoctrinating analysts into critical ways of thinking of high volume data in terms of relational algebra. Apart from AI/MO, even for operational research, relational algebra is available in 4GLs like Python, but it's far more expedient in SQL (and is the focus of SQL). Once you have experience in the concepts and practice, you can battle the syntax and navigate the APIs of Python packages, but trying to do both can stunt progress in both.

Also fully agree that technical skills need to be complemented with domain knowledge.

U r not in a Position to predict the future od data jobs.

Im a recruiter specializing in data and AI roles specifically in the BFSI space. I appreciate her analysis. Let me add one piece of advice. Companies want data employees to show they can last at an employer longer than 18 months. Stop the job hopping. I know too many highly talented unemployed people that moved too much. Now they are in trouble willing to take whatever they can

thank you so much for the info, pls do a notion tour💫

How to to become a data analyst is the question lol.. Google certificate program?

Hi Thu, I am a Financial Advisor learning programming to enhance my analysis! I love your channel! I am launching my podcast to teach financial literacy to diverse communities next month! I know it may be confidential but I love your B-roll / background edits I have been trying to find an editor for so long. Could you point me in the direction of your editor or ai you use? I do not mind paying for this information!

Hi hello I'm a Statistiction. How to contact you I tell to you some important thing

They lie. Electricians make more money rhan data analysts. And they start accumulating wealth earlier. And they have no student debt.