Highest Rated Comments


astromaddie33 karma

Manhattan is still a living, breathing, city without empty buildings or fake grocery stores. Even the "outdoor shopping mall" on Times Square is a real commerce district that millions of people use.

Look at the lights in that apartment building on the right. Notice how many of them are on in a consecutive row or column. You'll never see that in an apartment high-rise here; that looks like the occupants were probably (lazily) "scattered" throughout the building to give the illusion of higher occupancy.

astromaddie13 karma

Hey guys! OneNote is a really cool piece of tech, and I've been starting to get used to switching over to it for notes at work (the cross-syncing is super useful for my laptop and tablet).

Out of curiosity, while there's obviously no "wrong" way to use software like OneNote, it's a pretty versatile blank slate-- so, what's the most innovative, creative, or just flat-out bizarre usage of OneNote that has surprised you from users or test groups?

astromaddie4 karma

I can actually give some help to this! I have a physic BS and four years' experience in astronomy research, much of which was data science-related. After 7 months of job hunting and interviewing, I start my first data scientist job on Monday!

Basically, create a resume (not a CV) that de-emphasises your research material (which wards people off) and exemplifies the pure at a science you did. Talk about accomplishments, not tasks (e.g., "optimised a computer model using linear regression forecast modelling" rather than "performed linear regression modelling"). The bulk of your resume should focus on things you achieved, and unlike a CV, keep your resume at a page or so in length. ALWAYS attach a cover letter that will quickly gab their interest and defend why you, lacking direct work experience, are more than qualified for the position. And then, if you get an interview, consider they already think you're worth pursuing so you should relax, charm them, and make a persuasive argument for how your experience applies.

Also, I recommend learning R, SQL, and SAS in your free time.

Ninja edit: You'll face rejection. A lot. Even for positions you are ABSOLUTELY qualified for. Data science is a new field and far too many companies just want to hire business/economics graduate. But just keep on it, look for more startup-y companies that hire based on intelligence rather than experience, and you'll find something!

astromaddie1 karma

I'm gonna chime in to this too, because I have a borderline weird love for Python. Not only is it easy to clean, parse, and modify datasets, but the language is remarkably natural to write, making it drop-dead simple to write lengthy, complex codes with a ton of flexibility. You don't have the low-level resource access that you get with C or C++, so it's not as optimised or efficient, but when it comes to array manipulation, mathematical operations, statistical analysis, and data visualisation, it's fantastic.

And R is basically a simplified version of Python, so once you learn Python, R is even easier to pick up.

astromaddie1 karma

It's very ideal! If you ever want to get into real deep programming, you'll want to pick up C++ or something, but Python is a great gateway language.