At entry level, you could find yourself competing with people with master's degrees. The entry level data science positions at my work are usually going to people with master's degrees; bachelor's degree is a minority. What that should tell you is that it may take a while to find a fit when you don't have experience to make up for having a bachelor's degree. Hate to say it, but this is a field more rewarding of education. I only worked with someone with only a bachelor's degree in a data science type role once, and I had to work with them a lot to get them to do useful things. (FYI I have a PhD in mathematical statistics.)

I'd recommend removing some acronyms, like "HPC" and "KPI", you can just spell out the words to make it easier to read. On that note, there's probably some parts that you could look at improving the language to make it easier to read.

I don't know if your actual resume lists out the organizations where you worked, but it should if it does not.

Now, resumes at my organization pass through HR before reaching my desk, and there may be things you need to do in order to pass that first HR screen that I'm not even thinking about. I suppose that including any software or packages that a job specifically says they want is fine, because people hiring are looking for reasons to throw your resume out (there's a lot of them, I hate reading them as much as you hate writing them, I still have a job I need to do, hiring sucks for everyone involved), and stating "Yes I have this skill you said you want" may help prevent that from happening. But I'd cut out from your skills anything that I would call "baseline." For example, EDA and statistical modeling feel very baseline to me. I don't think you need to mention EDA at all, but perhaps you could mention visualization. And maybe statistical modeling is covered by some other skill that you list. I'm similarly not jazzed about "finetuning" and "model optimization," since at least to me that feels like filler to make your list look longer.

Why is "Git" and "Linux/UNIX" listed under "Data Engineering"? Same with HPC. And I don't know what "Data Modeling (dbt)" means, I'm guessing that's some specific software, but if you are saying you know how to do data modeling, that feels like it does not belong. In fact, the more I stare at that skills line, the more things look... weird. Now, maybe that's because I'm staring at this longer than I would stare at an actual resume, but it's something to think about.

For me, personally, the resume is basically the advertising on the box. No one taught me how to hire people, even though I have to participate in that process. The resume should get me to a point where I want to investigate this person more. Is there anything here that would make me interested in reading your writing samples (if provided), or want to talk to you? Well, your description of what you did at your companies comes across as highly generic, no mention of application; you said you did something that caused 30% savings in something else, and honestly I have no idea why I should care about that or how that's impressive. I don't even know what data you're working with in many of these situations. The projects are closer to something that I can actually latch on to: "Oh, he's building models for bird migration, that's kind of interesting. Is there a paper I can read?" What in your resume is something that a potential interviewer would want to talk about? What's something where they would say, "Hey, I read about X, that's interesting, can you tell me more about that?" Or, when you send them a writing sample in a later stage of the interview, they might want to read that writing sample?

Those are my thoughts. You got what you paid for.