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Anonymous

14 Nov 2020

Career

What do I need to do to get a job as a data analyst or data scientist?

I’m starting a part time mathematics program and it has an honours option but requires a 3.5 GPA. So I’m not sure if I shld work towards that goal for the GPA.

  1. Is a bachelor with honours needed to boost my chances of getting the job?

  2. If I don’t get honours, would it help getting a bachelor with minors? Let’s say my bachelor is in the science field and my minors is in arts field since I heard in the news that liberal arts is getting more important.

Discussion (1)

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For qn (1) yes and no depending on the employer. for jobs in the public sector, honours definitely affects starting pay from what I’ve heard.

for qn (2), also yes and no, depending on whether you want to actually become a data analyst in media/creative industry, even then you don’t need a minor in arts. I majored in science and I started in the fashion industry.

Currently in tech doing data analytics, so if you are serious about going into data analytics/science work, I recommend you to focus on the technical skills like SQL, Python, Excel/Sheets and Powerpoint/Slides. There’s no need to fret too much about GPA or which courses. The caveat is you must have enough side or personal projects or internships to actually showcase you really do know your stuff, otherwise GPA becomes the only indicator and a bad GPA will set you back at the starting line. Anyway, GPA becomes useless after your first job.

Why are the skills important you might ask?

SQL - extract data + clean data

Python - clean data + automate pipeline

Powerpoint / Google slides - present + communicate data

Excel / Google sheets - share data to business users

Mathematics and Statistics - challenge your data and assumptions (since you’re alr in a math program you shld alr have this by default)

This is the minimum requirement for a data analyst. If we’re talking about data scientist, then one would also need to know how to properly formulate business problems, scope the solution, ML concepts to understand the tradeoffs between models, select the right one and finetune features/hyperparameters, cloud platforms like AWS for CI/CD and some data structures as well for scale and speed of delivery.

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