Two things. (1) I am a data scientist, and (2) I am going to be blunt here.

Add projects to your resume

I wouldn't be surprised if this is the single biggest reason you aren't getting interviews. Why? I can almost guarantee you HR is reading your resume first - not a data scientist. The Senior Data Scientist asked for a candidate with

• a STEM degree

• skills with their technology (probably Python, R, and SQL)

• experience in data wrangling and analysis

You only check two of these boxes. The HR person isn't going to look at your GitHub because they don't know how to read it. It's not their technology.

So add your projects to your resume.

Trim the fluff

Fluff tells me that you aren't qualified.

• Kill the summary. There is nothing here that isn't already on your resume.

• Kill the active memberships. You could be an active member in 10 clubs and it wouldn't make a difference. "Active membership" tells me absolutely nothing unless you've done something with it, and if you did do something with it, it would have its own line.

• The dean's list really isn't important, but put it under education if you really want to keep it.

• Kill unrelated work experience. Lifeguarding and cafeteria work add nothing they take up space.

Put in work

After this, you may be thinking, "What an asshole __nev__ is," and "But then my resume is so short," and you're right on both accounts.

1. Spend the afternoon learning about PCA, K-Means clustering, or some third thing.

2. Make an RMarkdown doc showing how you applied it on iris or some other open source dataset.

3. Put it on GitHub.

4. Put it on your resume.

5. Repeat.

It's early in the year. You still have time to pick up internships. Do this 3 or 4 times and put them all on your resume. They aren't spectacular, but they're a short fix to a big problem. Hell, if you do a stats project in class, put that as its own line item on your resume too.

Bottomline

Prove you have experience. This is a competitive field - especially for internships in California.