Which types of roles are gaining momentum in our field? What are the jobs that seem to be the most in demand and will continue to grow?
You don't have to know for sure, but I'd love to hear any thoughts.
What programming sub-disciplines seem to be trending up in terms of career options?
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I personally see a huge growth in data science / data analytics.
And this probably will grow. Amounts of user data, IoT metrics are growing and data driven business decisions will be made even more frequently. Also, this drives ML, AI too.
Data Science. Data Engineering. AR/VR. Crytptocurrency and blockchain.
If I were in college now getting a degree in CS, I'd be looking at those paths for "things I should be thinking about besides just passing my courses".
Unfortunately, Machine Learning.
Everyone here mentioned Data Science and honestly, I see it happening but makes me pretty sad nonetheless. ML has been able to do some pretty cool things but the question I keep asking is: has it been worth it? Google has been one of the biggest proponents of ML and I'll be honest; apps like Maps being able to give directions and projects like Watson at IBM are revolutionary and fantastic. However, on the other hand there are problems the industry has "solved" that didn't need solving in the first place imo. Things like YouTube recommendations and super targeted advertising. A lot of my problem with ML comes down to the data itself. Users are using a service with the intent for the service to do its job, not decide what we want to do. The rise of ML has put the algorithms in control instead of the user, and that's not tech I like using.
Thanks Sean for this input.
Besides buzzwords in tech these days, I may be wrong but, I guess you understand that differences between Data Science(along with Data Mining/Info retrieval), ML/Deep Learning, NLP and classical applied statistics are razor thin. Which means having a good training in one of those fields can get you a job in another.
Not to mention that in order to learn our preferences they have to gobble up lots of data about us.
Shameless self-quote:
Dumb algorithms make us dumb
Rémy 🤖
Machine Learning, Front-end/UI Dev, blockchain, Clojure, JavaScript everything, Rust.
I think the need for data scientists is because we're collecting so much data (storage is cheap) that we need someone trained to analyzing it on a big scale.
DevOps or whatever you'd like to call it; 'site reliability engineer' seems to be the hot new title from where I'm at as a newly-minted one of same, although it seems really to be the latest iteration on "make our app & data infrastructure work" previously known as 'release engineer'. I think that's in large part down it having become more than possible for a solo developer to run enterprise-grade kit for free or nearly so with minimal effort: servers and databases (AWS, Google Cloud, Heroku) version control (GitHub, BitBucket), next-gen build tools (Travis, CircleCI), even metrics (Coveralls, PackageQuality). That's done a lot to bridge the gap between development and administration and made the synthesis of the two a compelling specialization for organizations big enough to need specialists. System administration as a separate discipline is never going to die out but more companies will be trying to hold off on investing in it when they can farm that out to the platforms and hire people who can work on the core product too.
Functional language development is having a moment and I'm hoping it lasts. Odds seem good, but it's still not as easy to find jobs working with these as it is to turn up the old standbys of Java, C#, and PHP.
Data science seems like a gold rush with some really neat things happening and a lot of really stupid things happening. I'm not outright bearish but I wouldn't be surprised if demand for analytics-at-scale were to recede some in the medium term.
Blockchain is an outright bubble. It's about to run into the NoSQL issue of "really, you need to know why you want to use this if you're going to commit" but much, much harder.
I wonder if and how serverless computing will change the role of DevOps. I'm already tired of the docker and kubernetes trend :D
I agree with you with blockhain, if it was ever useful Bitcoin and its creator have not exactly demonstrated how or why. My favorite article on the subject: Blockchain is not only crappy technology but a bad vision for the future
I think serverless (aka "someone else's server") isn't really a departure from the trend -- more cloud management, more automation, more build & deploy, less and less straightup administration. I don't see container orchestration going anywhere, I'm afraid ;)
I've seen a handful of compelling use cases for blockchain. One involved a distributed database of 3D models/CAD stuff where licensing, authorship, and versioning were all concerns. A peer-to-peer append-only ledger makes sense for something like that, but it's pretty specialized.
Blockchain seems like an inherently specialized tool. The grand generalizations seem really steeped in a capitalist gold rush.
Yeah, my naive hope is that serverless would make container orchestration another "auto" layer. You (as in devops) would still need to know how to operate on that layer if needed but you wouldn't really need to write Dockerfile(s) or figure out a way to monitor containers at scale.
Regarding blockchain... I agree, they marketed it (to companies and even consumers) as the next revolution in tech WAY before they actually had something revolutionary to corroborate such statement.
And if you cry wolf too many times... :-D I am sure there are people out there tackling problems the blockchain would indeed solve, I'm not sure replacing PayPal is chief among those (except if greed is your compass because you're not actually solving the trust problem nor helping the user experience).
Speech processing and speech analysis.
Computer Vision processing and analysis.
I wouldn't say any, but yeah, we collect too much data with the premise that one day it might be useful. Since storage is cheap we also tend to keep it for a long time if not forever.
You're right. I call this digital hoarding.
Wikipedia: Compulsive Hoarding
While my experience is limited and pure anecdotal, so take this with a grain of salt. The conversations that I have with employers, recruiters, and on a limited number of interviews surround a number of roles expressed here. Addition to those already mentioned there seems to be a lot of interest in experienced database developers; embedded device experience; and functional programming.
Titles that have gained traction lately, are embedded systems engineer; DBAs; and data engineering. Being from the Midwestern United States at a company with a lot of technical debt, I have also seen a need for folks who can support and adapt more mature technologies, so I could see a trend-up for people who know legacy systems.
Also from the Midwest here and I’ve noticed a similar trend. There are a handful of companies that went with “modern” (read: trendy) ideology and architecture, but a vast majority of them still stick with what has been known to work in the past. They stick with what skills local talent has in abundance and the local talent develops those same skills in order to find a job, or move to a different area.
It seemed like a downward spiral to me for years, but I think it has recently begun to evolve and challenge the status quo of “it always worked before”. Was it due to Agile becoming tried-and-true, the economic downturn of 2008, or maybe something else triggered a primal fear and need to change in order to survive? In any case I’m glad I’m around to see it.
ML/AI & Big Data Engineer
Blockchain - Contract (ethereum&others) developer
DevOps specialization in Cloud
More C++ switch to Rust, the others to Golang :))
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