Managing a transition into software and/or data science in your 30s

The Something Awful Forums > Discussion > Ask/Tell > Business, Finance, and Careers > Managing a transition into software and/or data science in your 30s

Suspicious Lump: Mar 11, 2004

"Learn Stats" is such a nebulous thing to say. Any more info on what kind of stats to learn? What are good resources?

Currently undertaking the Data Scientist specialistion on Coursera and it's stats heavy but feels like I need more indepth study. Any help or advice?

# ¿ Oct 4, 2017 03:20

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# ¿ May 22, 2024 17:38

Suspicious Lump: Mar 11, 2004

ultrafilter posted:

There's some discussion in the data science thread. That has a larger audience than this thread does, so it might be a better place to ask for recommendations.

Thanks didn't realise this exists.

# ¿ Oct 5, 2017 00:44

Suspicious Lump: Mar 11, 2004

I've done several of Johns Hopkins Data Science courses. They're great but are not easy. They except you to be able to troubleshoot most of your issues you will come across. My only complaint is some of their "courses" are really dumb, like the first one. They also have a few that can be hotswapped if youre into biostats. My goal is to complete the whole specialisation. But a word of warning, most people (it seems to me anyway) use python for data science. But R is king for statistical analysis and data wrangling.

# ¿ Nov 17, 2017 07:26

Suspicious Lump: Mar 11, 2004

Python...and R.

R is not a programming language. Well it is, but nobody learns R for it's programming side of things. They use it for the functional programming aspects, data analysis and computing. If you learn programming in Python and data analysis in R, if you ever join a workplace that uses Python for analysis then the switch over will be fairly painless. IMO It's not the actual words on the screen that really matter but the concepts. I helped someone on Reddit analyse something using Python + pandas but I had never used pandas. The syntax was somewhat different from R but the concepts were the same.

FYI I am not a data scientist (yet!) but I am working towards becoming one. Have a look around at future employers and see what they're asking for. Most companies in my city (Australia), seem not to care all that much about which program.

# ¿ Nov 21, 2017 04:46

Suspicious Lump: Mar 11, 2004

Vegetable posted:

What's his background?

Physics, mathematics, statistics, engineering, pick one.

I had a friend go from wet lab science with no programming experience to a very junor bug hunter at a company making ~$50k a year (min wage in Australia is $35, she lives in an expensive city). She completed one of those bootcamp but mentioned that nearly everyone else had prior programming experience.

This is realistically the best possible outcome after a boot camp.

# ¿ Jun 20, 2018 01:52

Suspicious Lump: Mar 11, 2004

Xguard86 posted:

once you're in the industry the key is you keep learning and stay aggressive on the job front. Tech isn't the meritocracy everyone wishes it was but 50 to 120 is easier than 0 to 50, if that makes sense.

Agree completely, the first step is very hard. It's just that I've seen many many posts of how someone has made the jump to programming/CS but when you find out their education you realise it sets them up perfectly for the field. I'm hoping to make the jump as well and might do a bootcamp just to network and nothing else. I have programming experience but in a very niche area (bioinformatics). No idea how I'm going to go, but I'm more suited for data scientists/analyst than actual programmer.

JIZZ DENOUEMENT posted:

Theater / service industry

That's amazing journey tbh.

# ¿ Jun 27, 2018 06:22

Suspicious Lump: Mar 11, 2004

So probably a silly question but apart from extracting data from a server, is SQL used for anything else? I'm trying to understand why SQL skills are so sort after.

Jon Joe posted:

I have a Master's degree tailor made for doing data science but because it's not named data science but instead psychology nobody ever believes me and I have literally never gotten a data science interview in *checks* over a year despite having used Python, R, and SPSS to comfortable levels.

Any advice?

Possible because quantitative vs qualitative analysis differ? Either way, you need to highlight your statistical skills and how they apply to the job you are applying for. Also, "comfortable" levels might not be enough to land a job. IMO (take with lots of salt) It's not the language but the statistical knowledge that's more important. I'm decent at programming in Python/R but my stats knowledge is not great.

Suspicious Lump fucked around with this message at 07:09 on Jan 6, 2019

# ¿ Jan 6, 2019 07:05

Suspicious Lump: Mar 11, 2004

Thanks everyone for answering my silly question. I had no idea you can push some of the computation to the server, that's super cool. Now to go find out how to gain some SQL skills.

# ¿ Jan 22, 2019 06:24

Suspicious Lump: Mar 11, 2004

Bootcamps do work, but not how most people think they work. Their main function is to allow candidates to network with prospective companies, what you learn along the way is secondary. That's my take on bootcamps.

I had friend go from no programming experience to working as a junior QA in a software company. From speaking to her, the bootcamp she did covered a large amount of topics in a very short time frame. Which means you don't get a lot of deep knowledge on one aspect. No idea why she jumped careers, she was making more working as a research assistant.

For me, every boot camp I come across always seems to focus on the wrong aspects. For example, data science bootcamps IMO should be stats heavy, programming light but they always seem to flip it. But the ability to meet potential future employers is just so tantalising.

my 2c

# ¿ Jan 28, 2019 07:58

Suspicious Lump: Mar 11, 2004

meanolmrcloud posted:

My current field has very little in terms of forward earning potential, so I signed up for a 6 month after work boot camp that I am nearly done with. It�s been a pretty cool experience, but the emphasis is absolutely on networking and a broad, quick overview with the expectation that you will invest yourself on your own time to really nail the concepts. I�ve just gotten to the part where my resume and skill level has been cleared to start applying for jobs, and we will likely being our big �final project� in the next few weeks.

How much did part-time bootcamp cost you? I've been considering this option actually.

# ¿ Jan 28, 2019 22:59

Suspicious Lump: Mar 11, 2004

MickeyFinn posted:

My lord, The Data Incubator wants me to post a video to YouTube giving them a 1 minute presentation. They also want me to give them the data I scraped. I'm starting to think this might be an actual scam instead of just employment grift.

At least Insight had a poorly designed email-you-a-minute-before-the-interview system where they didn't ask you to debase yourself to the data gods. I'm getting really sick of "failing" these interviews for reasons that have nothing to do with my ability to do the work.

You can find other people's submissions on YouTube! This is amazing.

They have a question on data exploration with really straightforward questions that require minimal understanding of what data even is. And a cargo cult linked-list question similar to cracking the coding interview.

Please continue to post about your experience with The Data Incubator. I was considering applying for this after I graduate but now I'm seriously reconsidering. It's really bizarre the hoops they're putting you through.

# ¿ Feb 3, 2019 05:53

Suspicious Lump: Mar 11, 2004

MickeyFinn posted:

I'm now also seeing entry level job postings that say work in academia doesn't count toward experience.

This has to be the weirdest thing I've read. Why would entry level jobs require previous work experience and why would previous work experience not count? Not doubting what you've found, doubting the logic of the company. :wtc:

Also, thank you for all the TDI posts you've made in thsi thread. Hilarious and scary at the same time, I was considering them after my PhD but now I'm staying the gently caress away.

# ¿ Feb 20, 2019 04:38

Suspicious Lump: Mar 11, 2004

zmcnulty posted:

So I have couple questions:
1) (for the company) If you could start from zero with your analytics framework, what technologies would you/wouldn't you use? Any best practices to follow? For the time being I am starting with the output, so trying to collect KPIs and figuring out what sort of reports and insights management is expecting. I built some sample dashboards in Google Data Portal/Studio but apparently other companies in our group use Tableau for visualization.
2) (for me) Would going further down the data rabbit hole be fruitless for someone with STEM background, or will the (presumably) difficult experience of actually building out the models and framework be significant enough to overcome that? If the latter, while certainly not part of the traditional marketing skillset, I assume learning SQL, Python, and R will help me get more technical? Will 2-3 years be enough time to build those skills?

You're in a golden situation that I would kill you for, and I think a few people in this thread. Not only are you given (I think, from what it sounds like) free reign to experiment but the time/possibility to learn these skills. You need to start asking more concrete questions about what you want to answer. This means knowing what data will be generated, how it will be stored and what software you can/want use to analyse it. The next step is figuring out what the gently caress "action insight" means to your employer. Even descriptive analysis can be quiet powerful with the right questions. This also depends on if you have to setup the data gathering and database building or if you only have to analyse the data.

Unless you're a dumbass, I think most people can learn the statistical techniques used in model building. I would personally focus more on the stats side of things and go easy on the programming aspect, this will come naturally as you learn more and more. Choose one language and just stick with it, don't hop until you feel comfortable in that language. IMO R and python are very close for data science, but R is better at visualisation/data wrangling while python is better at machine learning.

You can learn a lot of in 2 years, then hop out and find another job.

# ¿ Mar 11, 2019 01:31

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# ¿ May 22, 2024 17:38

Suspicious Lump: Mar 11, 2004

meanolmrcloud posted:

Quick update! My bootcamp ends this week and it looks like our project will be good to go on �demo day�. I accepted an offer from one of the bigger companies in the area, pending a background check. It would start at nearly twice my current salary, though I do have to give up a lot of flexibility and work the 9 to 5, whereas now I probably only work about 30 hr per week.

I suspect that the bootcamp itself is pretty heavily involved in the process, as the HR manager at the bootcamp has been recommending specific people to specific companies where he thinks they would be a good fit. My interview with them went pretty dang well, and they seemed to know what level of technical questions would be best to still be a challenge, probably because they are fed a lot of bootcamp grads.

Did you mention what bootcamp you are/were doing? Can you tell us?

# ¿ Mar 20, 2019 05:03

The Something Awful Forums > Discussion > Ask/Tell > Business, Finance, and Careers > Managing a transition into software and/or data science in your 30s