Data Science Era |OT| Desktop BI, Deep Learning and Everything in Between

Oct 25, 2017
3,340
Yeah it was a report designer, we do some analysis in our group now, but the nature of our structure and using Data Warehousing is different, and you can still do raw SQL pulls against it, we just happen to have several BI tools that make it so you don't have to. We can't teach our 5000 users SQL and most of them don't have the time. So we are reliant on doing good ETL and making sure we work hand in hand with the business to ensure we encompass all of their data needs. It is still a tried and true DW model.

A lot of the time our data marts are just massive relational star-schema DBs with tons of data and a lot of ways to dive in to it. Other times it is already very sliced up due to business rules.

I get what you are saying for sure though and I agree, you want to avoid a lot of assumptions. Especially going forward in analytics you don't want a lot of those presumptions. And when I say I have an ETL dev create a view, it is literally just, get me these four tables from DB A, these four from DB B and these 6 from DB C and give me these joins. It is what the guy does all day and he can turn around a MV real quick and then I can go in and pull in that data to my tool and do the actual analysis with no preconceived assumptions.

Also, just in general, I feel like the more and more I get exposed to new concepts and the way other companies operate in Data Science and Analytics, the more I think my current company isn't completely doing it right or completely understanding new concepts. I want to keep building and growing in this, but man it feels like they are missing the boat.
 
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Oct 25, 2017
2,194
California
I'm questioning whether I should continue my solo learning path on data science. Over the past two years I've learned and practice enough data analysis and machine learning to get a job but I have no intention of getting a Master's or PhD nor do I have the time or money. It sucks because I love this field but I want to make a career out of it. I love how easy it is to learn on your own.
 

Pau

Self-Appointed Godmother of Bruce Wayne's Children
Moderator
Oct 25, 2017
1,602
This past month has been a whirlwind.

I got rejected at one program, then accepted into three, and now I'm waiting on two more.

I honestly thought I would get accepted into one at most, so this is incredibly surprising. This is going to be such a hard decision to make, but the good kind of hard. I have until mid-April to decide!

Anyone have experience with or considering Masters in Data Science at Harvard, New York University, or University of Washington?

I'm questioning whether I should continue my solo learning path on data science. Over the past two years I've learned and practice enough data analysis and machine learning to get a job but I have no intention of getting a Master's or PhD nor do I have the time or money. It sucks because I love this field but I want to make a career out of it. I love how easy it is to learn on your own.
What's stopping you from applying to (and eventually taking on) data science jobs?
 
Oct 25, 2017
851
Definitely pick NYU if you want to do cutting edge machine learning like deep learning stuff. They have both the faculty (Yann LeCun) and the connections. Not sure about Harvard but program looked quite technical last time I looked at it. No idea about University of Washington.
 
Oct 25, 2017
851
I have the practical knowledge and experience but I feel like my lack of a formal education would essentially disqualify me from any data science position.
The amount of people with "formal" data science education is pretty small, since most of the data science programs are pretty new. Most data scientists came from and are still coming from other fields. So if your experience or educational background had a good amount of exposure to statistics and programming, then you're in decent shape. Of course experience in this field are highly valued, but as long you're not picky and you really want to enter the field, it's definitely doable. You just have to think about how to showcase your interest in your resume to stand apart from all the other people also applying for the same job. That could involve talking about some Kaggle competition you attempted or other kinds of data science exploration you did by yourself.

On the flip side, data science in a lot of smaller and medium-sized companies still requires a lot of analytics skills (which isn't really taught by any course and education) and experimentation skills are often far more useful compared to machine learning skills. That fact may be something the companies don't even realize themselves as they attempt to build their data science teams. Can't argue about the wealth of opportunities that exist though, definitely worth it if you're interested unless your current field is already pretty nice and comfy.
 
Oct 27, 2017
47
I have the practical knowledge and experience but I feel like my lack of a formal education would essentially disqualify me from any data science position.
I suspect most teams are like my team, in that they have a wide variety of roles and levels. I hired a guy with no experience in enterprise analytic tools (he knew sql) into a junior role a couple years ago, and he has absolutely blossomed. He’ll get his 3rd promotion this year, and will probably be my boss in under 5 years.

This is a path my team continues to follow today as junior positions open up. While it might not always be as successful as it was with that one guy, it is also a path I took when I joined the team. Don’t count yourself out, just look for the right analytic position, on the right team, and you’ll get your foot in the door.