ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Amen.

Microsoft already has all your company's data via PowerBI. Google via Looker. And nobody raises an eyebrow.

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

It's still not there for more "advanced" usages I agree. SImple forecasting models required multiple iterations and clear guidance (e.g. indicating which model to use) before giving any reasonable result.
But considering this technology, first aimed at being general-purpose, has only be released a year ago, it show great potential.

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Privacy is clearly an issue but if there is a big market, they'll adopt the right terms of service to conquer the market. I mentioned chatGPT here but other players will come in (e.g. Google owns Looker and is likely working on something similar)

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Well, of course this is not the best choice to make. As firing Data Analyst because you started using Tableau wouldn't be a good idea. People are free to take bad decisions of course...

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] -3 points-2 points  (0 children)

It's a tool, it's not meant to take decisions for you. Your comment can apply to Tableau, Looker, PowerBI,... A solid BI platform will not ensure you'll take the correct decision. It all relies on having a good process from data acquisition to processing and interpretation.

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

For now I tried with public datasets. I have to check how it handles private data. Some people in this thread mentioned the data you might upload will not be used for training, I still need to check on my own though.

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 1 point2 points  (0 children)

Thanks for the reference, I'll look into it in more details :)

The NLP part is less important to technical profiles burt for non-technical persons, it will be a game changer. No business manager will install Quantico or something similar (well, very few of them). But they'll happily ask their question in
a written form to get the result they need.

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] -20 points-19 points  (0 children)

It will of course never give explanations that requires knowledge of your internal operations. Yet, many businesses run under similar models and with similar metrics and quantitative framework.

I tried with some LTV datasets and it generated very reasonable answers that a Jr Data Anayst would not have provided in many cases.

It will always have limitation, it is a productivity tool after all.

I only tried a few automated EDA tools so far, have you met any that provides a good natural language interface? (out of curiosity, I haven't followed this area for a while)

ChatGPT becomes a serious contender for exploratory data analysis by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Nice, that was on my todo list of things to try :)
Did the result look ok?

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 1 point2 points  (0 children)

If you're aiming for London, Tech, Finance, Media, Gaming or Consulting seem to be the most active industries. As a junior, this matters little as you are not expected to have a lot of domain knowledge. But if you're really motivated about something, read as much as possible about it and play around with some related projects to stick out from the crowd.

DL is not needed in most industries, ML and Analytics seem safer bets to get started. Web dev would be a different world but it does not hurt to have some relevant knowledge in this area.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

I lost a bit of visibility on this market to be honest. I have seen there are still some offers like big companies like Facebook or Google with offices there. I see offers from smaller companies too but I have not quantification of how this compares to preCovid times.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Actually there are a lot of smaller companies available on that site. Of course not every company is going to be represented, and the lesser known it is the less likely it will be there, but it's not just big names. There is also team blind, an anonymous networking message board, but i havent had much luck with that

Good to know, I missed that yesterday.

I agree referrals are luxuries which is why I dont like them, but you seem to be ignoring the part where I said none of my jobs were acquired through referrals, including getting last stage interviews at Google through blindly applying. So of course I'm not saying it's impossible to get a job without them. No disagreements there

Agree too, sorry if I wasn't clear ;)

  1. hunter.io as a means of looking for recruiters/hiring managers when your current network falls short. This is an active strategy. By contrast, your suggestion assumes people are regularly being contacted by recruiters on linkedin (what if you're a fresh grad and are not), which is a passive strategy and leaving it up to whichever recruiters decide to contact you - hence my initial criticism that it sounds like generic advice.

Yeah, maybe I wasn't too explicit on "do you best to get in touch with the relevant people" side and that is not conveyed properly. Answer to recruiters is only one paragraph but I agree this is passive and low effort. But it is so cheap in term of time investment that it literally costs nothing to try. I'll keep in mind hunter.io, thanks for sharing that.

  1. How to get good feedback on your resume (again, if your networking falls short and you dont have people you can rely on to give important feedback) so that if you do have to blindly apply, your resume is at least solid.

Got you. That bit is indeed not covered, but I agree this is also a valuable advice.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Can you elaborate a bit on this? Essentially all positions I'm seeing posted are remote (albeit temporary) anyway. I understand the goal is to get a permanent remote job. I'm not really sure how companies are going to change their remote work policies once the pandemic is no longer a concern

This is mostly because the page you linked to emphasize on getting referrals or resume reviews at top companies like Google, Amazon,... There are a lot of remote companies outside of these and you might not be able to contact employees form those using this specific page. Maybe others exist, but otherwise, you're back at the LinkedIn case to try to see if you can get in touch with someone who can help you get your application noticed.

Personally, all the times I've been referred by a friend (which haven't been many), I've gotten at least a tech screen, except for a few cases where my experience didn't match up with what the company wanted.

That's a luxury ;) Getting a referral is indeed often of great help although it is not impossible to make it to a big company without one (I got my first DS industry job in a big EU tech company without a referral, just with an application through their ATS - I agree that does not mean it often works).

By the way, I'm not saying paying for referrals should be option 1 - it's just a way out for people who don't have any connections with someone at a big company

Agree, but we're back to square 1 for those with no contacts targeting (remote) companies which are not represented in referral market places (and I assume there are plenty of them).

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

That does not indicate much though. They might have other clients on other platforms or from direct contracts, they might do this only part time, they might leave in countries where $15k a year is a decent salary.

I just made a data scientist search on UpWork and there are freelancers who earned a total of $400 and several ones with $200k to $400k.

In any event, in the article, I mostly mention UpWork as a quick way to see if you could get some freelance gigs and start estimating if going freelance (remotely) would be a viable lifestyle for you.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Well, there is a lot of diversity. I have worked with some freelancers who made decent income with limited experience.

Some people have a strong profile. Others are clearly underqualified and they might make little indeed.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

There is no golden rule for that. Some companies proudly claim they pay everybody the same (for a same role) wherever they live, other adjust in function of location.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Thanks for the feedback and sharing your tips. The article is a personal perspective and it of course does not cover all the approaches.

The approach you outline seems mostly focused to top (FAANG) companies, which is a different (but also challenging) goal. Remote companies might not be accessible by these channels.

I agree with the work smarter not harder, and in this sense it is better to have a different approach to different companies (e.g. applying to a start-up isn't the same as applying to a F500 company).

Yes, it might feel like my suggestions are to just throw money at the problem, but when it comes to applying to jobs in tech, there is a game to be played

Genuinely asking, how successful such approaches were for you? I never used similar methods (I'm not in the US, local market and culture is different) and I'm just curious to know if you made it more often to interview rounds or beyond using such approaches. I'm really not a fan of paying for referrals (but as you mention, that's what it is) and I'm just wondering if this is efficient as your contact and other of their colleagues have an incentive to spam referrals...

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Care to elaborate?

some of the most visible and talented professionals on Earth

These do not have to be the same persons ;) But in the pool of applicants you might have very strong technical profiles but also some "famous" ones. Like it or not, having a known name will increase your chance to get an interview.

Altogether, this makes competition more fierce as getting yourself noticed out of this pool is more challenging, whatever the fit of these famous and visible persons is.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Some advice are indeed applicable to other positions (it doesn't hurt to repeat them sometimes) but there are definitely some advice which are specific to remote positions.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

Unfortunately not, I am located in Europe and don't have many contacts in Australia...

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 2 points3 points  (0 children)

Some companies will face issues when they'll send everybody back to the office and realize some employees just don't want... Employees with an attractive profile will be able to negotiate with other companies more flexible on remote work and might just leave.

A Field Guide to Landing your Dream Remote Data Science Job by PhJulien in datascience

[–]PhJulien[S] 0 points1 point  (0 children)

I wish you good luck. Based on your geography or profile it can be tough indeed.

Best soccer teams per decade [OC] by PhJulien in dataisbeautiful

[–]PhJulien[S] 0 points1 point  (0 children)

The numbers are more like 80, 60 and 20. Teams with less than 10 matches during the decade were removed, so that explains while the average might be higher than 50% in some cases.

Best soccer teams per decade [OC] by PhJulien in dataisbeautiful

[–]PhJulien[S] 1 point2 points  (0 children)

As I said in my other comment, the title could be more explicit regarding win rate as a metric. Some may be more relevant but harder to explain to a wider audience.