Hey guys, I'm a recent graduate trying to get into a Data Analyst Position. I mainly use Python, SQL, Excel for my projects. What would you recommend I add to the list to learn that will better my chances at landing a job? I don't have any experience this is my first tech job I am trying to apply for.

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If you’re into product analytics - consider spending some time and learning more about unit economics, product metrics, a/b testing (!) and other relevant topics. It won’t take much time but will boost your attractiveness as a candidate x10.

Also, as was already said above - git would be very helpful. Also, some visualization tools (any, really) would also help you a lot (Tableau should do the trick and is very easy to learn).

Also, build a small portfolio of cool projects to show and talk about during the interview. It’s always better to speak about something you built and know well /passionate about rather than make your interviewer figuring out what else s/he should ask. :)

PS I’m a hiring manager and ex analyst myself, conducted 100+ interviews (mostly product/data analyst roles as well as DS/ML engineering).

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Depends on what type of data analyst you want to be... If you want to skew closer to data scientist, I’d add Git and AWS (or something similar). If you want to be in a more analytics/viz type role, then maybe Tableau and/or RShiny?

But you already have some of the core technical skills, so I wouldn’t worry too much about trying to add new things to the list. Just make sure you have a good understanding of the tools you already use. And, either way, definitely highlight any client-facing and teamwork skills.

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You have a fairly solid foundation already. There are a lot of things you'll be able to learn on the job. Have you already started applying for jobs?

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What kind of work do you have in your portfolio? Do you play with open source data and develop any kind of insight etc?

Congrats on graduating. I think getting hands on experience with what you have is more important than trying to add additional skills

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Make sure you have a foundation of econ/finance concepts & theory — often our solutions as analysts are ultimately applied to econ/finance problems.

Also statistics and how & when to apply different stats methods.

Your skills are as good as how well you apply them, & you’ve covered most of your “data skills” bases with Python, SQL, Excel. Nicely done!

- AWS, GCP or Azure
- Git
- Basic Data Modelling

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