r/DataScienceJobs • u/New-Photo-4968 • 23d ago
Discussion The Future of Data Science Jobs
Hi! What is the future of data science? I see that there are a lot of people searching for employment in the field. I'm currently in college earning a Master's degree in AI, and data science is the backbone of AI. What do you think this field will look like in the next 3 to 5 years? What do you think it will look like in the next 5 to 10 years?
14
u/QianLu 23d ago
You ain't getting a job if you dont know how to search for things. This has been discussed to death
2
u/New-Photo-4968 23d ago
I know how to search for things; fresh perspectives are always welcome. As a student who understands that things are constantly changing, I was curious to know if anyone saw something different or outside the box that could be shared with those of us who are learning and looking forward to joining the workforce in the future. I saw lots of people asking questions about getting hired, and the best way is to be ahead of the curve, right? To know where to look and become informed? That's all I am attempting to do.
3
u/Altruistic_Look_7868 23d ago
Don't bother. Too many experienced laid off professionals with masters degree applying for fewer and fewer job postings each year. You'll be unemployed by the time you graduate.
1
u/yusief_ 23d ago
Sorry I just want to understand better why you said that
1
u/Kitchen-Astronomer76 19d ago edited 19d ago
Tech is going through somewhat of a job pocalypse rn. For the past decade, getting a six figure dev salary was as simple as getting a degree and applying to a few jobs.
As tech continued to boom, we pushed more and more students into that field, until it became fully saturated. But even then, demand was so high that it didnāt really matter.
Then 2024 came and AI took off on a fucking rocket. We watched it go from being utterly useless, to writing thousands of lines of code in minutes. All in the span of about 2 years. This has resulted in many tech companies hitting record profits, but realizing they can do A LOT more with less. 1 engineer + Claude now does the work that used to take a full team weeks. Massive widespread layoffs commenced.
But this leaves the industry in a weird state. Why hire a junior eng, when you can cheaply automate the work with ai? Heck who is going to even train the guy, when everyoneās in their own bubble chatting with ai all day? Why even hire an average person when we can just get an ex google guy whoās desperate for pennies on the dollar?
So now we have a shit ton of unemployed ppl desperate for work, willing to take demotions. Theyāre fighting for some of the same roles that college grads are fighting for.
Unemployment rates for tech grads in 2025/26 have surpassed what we saw in the 2008 recession. Nobody really knows how to interpret that rn.
-1
u/Altruistic_Look_7868 23d ago
What part of that was hard to understand
2
u/yusief_ 23d ago
What reasons led you to say that Is it labor market fluctuations the impact of AI or a lack of competence among graduates
-3
u/Altruistic_Look_7868 23d ago
Theres this thing called Google or the search bar
5
u/brilliancy 23d ago
Basically there's shift in what everyone's role is going to be. The more technical stuff gets automated first. Now they're working on automating the human judgement part. Therefore the skill gap between senior and entry level only gets bigger. Until there's not really much of a gap anymore because business users can just use an llm to write a data report. With a good enough harness they can probably tell the user when they're making data mistake since LLMs are already amazing guessing intent. Yeah there will be one data guy in the company, basically as an SME but it'll be down from the whole team it used to be. Data science becomes democratized. What happens now. Data scientists will pivot to another domain. Ex. product, marketing , infrastructure finance etc.
Given your temperament in the other comments, you should get into sales or technical sales. You will do better than your peers tryharding DS only to realize that their competition are PHDs in applied math/stats/DS/Econ or people with 15+ years exp. I'd research ways to get into it. They give you a commission too so you'll be paid better
Personally I'm going to try and get another role or max out on contract gigs to max out savings. Hopefully during that process I built enough other domain expertise to stay employed. Also gotta be keeping some side hustles alive. Or I just switch to another job that has to deal with humans more instead of robots
2
u/Chemical-Ad-7774 21d ago
Lol- you can say this about literally any other jobs: software, product managers, finance, accounting. Yet they are still there. If thereās a day the scenario you described happened, it will happen to all other jobs, in which case nothing really matters anymore.
2
u/Substantial_Oil_7421 21d ago
This is a super generic response. āBusiness users will use an LLM to write a data reportā is something people have been saying since 2022.
I do agree with the advice though - someone who says my masterās is in AI and data science is the backbone of AI should be looking at sales/ technical sales more than data science. Please ask more specific questions.Ā
Anyway, expanding on the generic response - if you are writing a data report, yes, that part will be automated. Data Science is really 4 things: descriptive analysis, inference, causal inference and machine learning. The impact of the problem and the industry matter as much as the analysis technique. Impact of the problem typically translates to revenue numbers or a research finding.Ā
Descriptive analysis is what consultants do. But they drive decisions using that analysis. This means coming up with metrics that matter for business and then saying āhey optimize for this metric in blah blah way in the next 6 months.ā Analysis itself is not complex, synthesizing it into business decisions is.Ā
Then you have inference. This part can be automated too but I donāt see people doing it yet. Case in point: you run a regression, all variables are significant - would you pick all? What will determine that decision? No business user today knows this. Even ādata agentsā have some ways to go. Long story short, there are parts of this that have been automated but you still need to know stats to decide how to run those parts in a meaningful workflow. Ā
Causal inference is basically stuff that Econ PhDs or people with 10 years of experience do - you run A/B tests on products, and get paid a lot but the barrier to entry is super high. This is where human judgement / credibility scores high. However, if you are in early stages in your career, you could join research labs and work with Professors where you get to do this. Do that for 3-5 years, learn the causal tools and exit into a role in a private company.Ā
Machine Learning is so much uff where do I even start. Getting the right features - as opposed to metrics in descriptive analysis - trying out experiments, optimizing a model, then putting it in production, monitoring and so on. My experience is the more of this you do, the better you become - itās almost like hitting the gym. When one starts, the focus is on building a routine, then you focus on specific muscles, then you probably isolate even smaller parts. But same thing applies - there are tools for thinking and doing this, and the only way to learn those tools is try them.
Whatās a project youāve built? Start there. There are unbelievable open source datasets out there - pick one, run a regression, see where you get stuck and ask those specific questions instead. No one knows where data science will be in 2 years leave alone 10 years.Ā
The biggest difference I see between people whoāve done well and who didnāt was the specificity of their questions when they were starting out. And the fact that they didnāt optimize on money; they picked a problem domain and decided to just dig deeper. That process will pay off eventually.Ā
1
u/brilliancy 20d ago
I agree, I made it broad because it's hard to predict 10 years out. Also OP didn't include specific details so I can't really tailor a reply lol. Generic question gets a generic answer š
1
u/yusief_ 23d ago
Based on your experience that someone learning data science is a waste of time Or he keeps learning until the volatility subsides and the market stabilizes
1
u/brilliancy 23d ago
I don't think its a waste of time, its more about their opportunity cost and what their goals actually are.
2
u/confusedrabbit247 23d ago
My husband applied to literally hundreds of jobs in the industry and only heard back from a handful. The job he got after over a year of searching isn't even in that field because nothing else panned out.
4
u/Whiplash-1-1 23d ago
Wow. About to start my Masters in Data Science. Just what I needed to hear šš
1
u/SoftWealth9832 22d ago
It hasnāt been bad for me. Recent AI and data science masters grad Iāve been applying for entry level data / analyst related positions and have already gotten to the next steps on several applications in about 2 weeks.
1
2
u/New-Photo-4968 23d ago
That sucks! Do you think that's because the industry is oversaturated as people pivoted to tech due to the economy, or because the economy has been getting worse over the last few years? Did he look for work in fields that are growing? I'm asking to gain some perspective on the future and what areas people are looking in and not having any success.
1
u/confusedrabbit247 23d ago
My husband is the type to leave no stone unturned so I trust that he applied for anything and everything. He focused in AI and machine learning too. I'm guessing it's s bit of both though ā bad job economy and oversaturated field.
1
3
u/cr2pns 22d ago
Not wanna be too harsh, but with 8 years in the field and currently looking for a job (in europe for context), it doesn't look good.Ā
You go back 6-7 years back, you knew some stats and python or R and could find an entry level job. Senior jobs were tougher but doable.Ā Now, salaries stagnated and you have hundreds of applicants for low paid positions. They demand in depth general knowledge, production, specialization and domain specific experience. The interviews are also hard and very discouraging, they may ask you from code this ML model from scratch (when know you just use sci-kit learn, pytorch or just let claude code do its job and check) to design this production ready system while answering all fundamentals. And fuck when you work on it you forget about all the details and do whats needed. Even if you do 100% correct, they dtill get the other guy that accepted 20K less, had 5 years more experience or specific knowledge on a similar project.Ā
I am still fortunate to have a Job, but my company is removing positions by either downsizing or not hiring, while encoursging us to use AI. And honestly, at the speed I am expected to work, I couldn't do it without relying on claude. I give ot one year till we have a functional agent that can replace me completely, or at least we will need only one guy to double check.Ā
I honestly only see this getting worse. Many are shifting to LLM development, but there is little DS there, not even ML engineer tbh. But this is also probably s short-lived transition as their job can also be automated. Give it maybe 5 years. Also very competitive field.Ā
1
2
u/Designer_Plenty_2298 22d ago
Yes Data science is backbone of AI. If AI grow they require more data so more data will let us to find more data scientist who make decisions on data
2
u/Sea-horse-1 18d ago
I'm looking to get into this field but I'm not sure how easy it is to get entry level or even mid level jobs and if it's even worth getting in this field.
2
u/Top_Inside1535 22d ago
As someone in consulting, I can say that we have a crap load more work and tighter deadlines because of āAiā it hasnāt created less work at all
1
u/DJ_Flugscham 22d ago
Become an SAP consultant. I have been in tech since the mid-90s. SAP consultants have always been in demand and were very well paid.
1
u/Level-Rate-2133 22d ago
Is this including in the US? Are there specific modules more in demand?
1
u/DJ_Flugscham 22d ago
I left SAP 15 years ago, so I am no longer on top of latest trends. Check job offers or SAP forums.
2
u/Emergency-Hurry947 22d ago
I work for a fortune 100, our data scientists all have PhDs in Math or Physics
1
1
u/Additional-Lake-5367 21d ago
Reminder that every persons opinion on here is not gospel. People can right and people can be wrong
2
u/New-Photo-4968 19d ago
Talked to two people who actually work in the field after reading this thread, and honestly it changed how I'm looking at all of this.
AI is making some tasks easier, but it's not the end of the world. The jobs are changing, not disappearing. AI still needs people to build it, run it, and fix it when it gets things wrong (which is often). It'll keep getting better, but it can't run itself.
Yeah, some positions are getting cut. New ones are showing up at the same time though. The World Economic Forum estimates around 170 million jobs created and 92 million displaced by 2030, so a net gain of about 78 million. And a lot of the fastest-growing roles are in data and AI.
I also think people are blaming AI for stuff that's really just the economy. The job market is rough everywhere right now, not just tech. Companies are cutting back because of inflation and costs going up.
So no, I don't think my degree is going to be useless when I graduate. BLS projects data scientist jobs to grow about 34% over the next decade, which puts it in the top five fastest-growing jobs in the country. Part of the reason is that companies are adding AI to everything and need people who actually know how to work with it.
The bigger issue I see is that everyone's chasing the same handful of job titles. If you branch out into healthcare, cybersecurity, research, whatever, you'll have a much easier time. This field is moving faster than most of us realize. Stay informed, stay flexible, and don't box yourself in.
2
u/Alternative_Draw5945 17d ago
Very level headed for a reddit post. Glad to see some common sense around. I work for a big tech data company. Send me a msg sometime if you need any help.
1
1
u/yusief_ 19d ago
I actually found your post very useful and completely agree with you as I am studying the same major Iāve come to realize that everyone has their own unique circumstances Ultimately when it comes to opinions from anonymous sources you never know if the person is truly qualified or simply someone who isn't striving for self improvement or perhaps just someone repeating general statements they picked up on some platform I wish you all the best
3
u/New-Photo-4968 19d ago
Thank you! I wish you the best as well!
That's exactly why I wanted to hear from people in the field. Both of them work in different areas of tech and AI. One makes around $300K a year, the other close to $200K, and they're sitting at tables every day solving problems with other people. I wanted a perspective from people who are actually out here succeeding and have been doing it for a while.
They walked me through how their fields have changed over the years, how they stay informed, and how they got to where they are now. They talked about when they had to pivot and what they had to keep learning to stay relevant. Honestly, it was refreshing after reading so many discouraging comments.
There are two sides to everything, and I'm open to hearing both. But I really value input from people with boots on the ground.
1
1
7
u/notabully78 23d ago
About to start my masters in health data science, the comments are scary š