Hi guys, Thanks for watching. I would love to hear from you, what are the sad realities you’ve experienced as a Data Scientist. Don’t Forget to like and Subscribe.😊
Bro getting job as a fresher is difficult in ds So I decided to for data analytics gain some ex than jump into ds.but the thing I don't like visualization part .like tableau but rather only interested in ml,dl, part So should I still go for da or other tech gain some ex and then jump into ds?
1. If you didn’t plan to always be learning, you’ve chosen the wrong field. 2. Unless you’re in an extremely mature organization with highly segmented labor, you will almost certainly have to play the role of facilitator. If you want to be a staff or principal level researcher, you absolutely must do this anywhere. 3. Following 2, nobody cares about your tech skills, they care about the value you produce. 4. Your real job is to create order out of ambiguity. 5. If you’re good at what you do, the market is ripe with opportunity right now. If you don’t have experience, it’s brutal.
@@enjoyourjoint5012 Try to do data analyst or data science projects in your current jobs. Try to get your hands on data, excel, csv files etc, then do a project. If there's no data, try to think of some trends or analysis that would be useful. This will give you hands on experience and you can put it on your CV.
What's wrong with constantly learning and challenging yourself? I I agree with unreasonable expectations, which no one wants to do. But if you're not constantly learning and challenging yourself or don't want to, then you're in the wrong field of work. If you're only in for the money, which, nothing wrong with that, then find a simpler career. Going into computer science and not challenging yourself to learn more or stay update with technologies means you're behind and probably that guy getting put on the chopping block when it's time for layoffs.
The best approach is to follow the TH-camrs who specialize in the tools you choose. So as you regularly watch their videos, you are indirectly being updated on tech as well.
As a current data scientist, I agree with everything you’ve said but also with a few comments as well. Tech in general we are expected to constantly learn/upskill and that can get tiring after many years
its the always and forever learning and adding skills that is the most difficult part i found out about . This is not how i imagine my future to be like when i was 20 and starting in the field . I wonder if anyone feels soulless at times
This is why I want to get out of tech. Being on the training treadmill is tiring. I understand that every career needs Continuous learning, but tech is a different level of upskilling, and it gives me anxiety.
I left the field after 30 years. The field is much different now. Ultimately, I was working 6 or 7 days a week. I couldn't take it anymore. It became unhealthy in many ways.
@@jegathingsbelieve me when I say there are days I stay up just to finish a project. Tech and especially in the field of data science, most people don’t understand how tiring working on a project is, they expect results in few days which is impossible. I love data science but people who don’t understand is what’s getting me on my nerves. It’s different than other fields.
Software engineer turned data engineer eyeballing data science and this was helpful. Honestly I feel the same now with the overwhelming amount of tools and knowledge needed but it’s hard to complain when it feels more doable than say mechanical or electrical engineering. Anyone else feel this? Not imposter syndrome just honestly. It’s hard work and very demanding. Just different than other disciplines. Anyways I’m kind of bored of constantly learning a new tool every month or so. So I’m focusing on mastering things I enjoy and screw the employers and even other competition. Not worth my health. Gotta be smarter not work harder right!
It is crazy. I am a trained data scientist, but I build ETL pipelines, dashboards, some software engineering commitments all the while working on my communication skills. It is a lot to do, and while I am not really bothered by having a lot of work, the pay is ridiculous! I am highly underpaid and it is frustrating!
First time here, am also a Data Scientist. I currently work as an instructor at a computer school teaching data courses. One of the lessons i picked from this video is that as a Data Scientist, u have to keep learning and its true. Sometimes, i feel as if am not trying. Thanks for making this video
I find your advice to be equally applicable to my role as an Excel specialist. There's no end to the learning, which is a positive for me. The most important skill, assuming one has the fundamental technical skills, is people management. Managing expectations will get you further than technical expertise...
Continuous learning is a prerequisite for nearly every career realm where high-value assets contribute. I’ve squandered countless hours down the rabbit hole in overhyped courses with clueless facilitators just rehashing definitions without any real-world applicable examples. It’s refreshing to hear someone tell the truth. 👍🏾
I found your clear explanation incredibly inspiring. It motivated me today as I continue my journey in data science and machine learning engineering. Thanks so much sir
I studied Data Science in 2014 and got a job in 2015. I worked for a year and quit because of too many demands and I saw that in the future there will be less job. It was a good decision I made then. Nowadays it is better to be data engineering and upskill yourself and follow the job marketing trends.
The always learning part is what is unpaid and you gotta do on your own time, compare that to other job roles that pay just as well where you're not required to learn new stuff. Essentially you're learning new things as your older skill becomes worthless.
@@dallysinghson5569 then you're in the wrong field of work if that's so troublesome to do. You may not be getting paid, but you're growing yourself and opening doors.
@@dallysinghson5569 In saying this, I do not mean to know more or better than you. Like your view, this is just another perspective. It is a sigh of relief that new techniques, new stacks, etc. are periodically released. It is true that they add work & challenges, but they are a constructive kind of work. We could get accustomed to kicking the butt of the same video game, playing it over, & over, & over. Fortunately, other devs are cooking up yet other video games to alter the look & play of existing ones. Loosely putting it, essentially, all video games are one & the same, reshuffled, reconfigured, resized, reimagined. We appreciate the classics while we also anticipate the new worlds that new games unfurl.
The key is having the appropriate degree and understanding the theoretical underpinnings of data science. If someone graduated from a boot camp, then they are at the mercy of learning tools or the technology and this is never a position you want to put yourself. If you’re truly serious about being a data scientist, you should have at least bachelors degree in applied statistics or something similar and better a masters degree, once you learn technique and the theoretical underpinnings of the discipline then you become much more resistant to change and it is much quicker to pick up new technologies because you understand how they inherently work .
Great video! Commenting so that it reaches people about to start out it data science and aren’t being told how competitive and challenging it is Haha landing a role as a data scientist is super challenging! And you always have to keep improving. On top of that if you want to get promoted you have to not only be the most technical person in the room but also one of the most business savvy. Man on man is it a hard role to fill! But that’s why everyone wants to become one, because it’s a role that gives you purpose and pays well
seriously i started hating my job as a data scientist!! companies bucket list is increasing like hell. Trying to change my company but not a single profile matches mine.....they need almost 90% match.banking sector will not take engineering data scientist. Healh sector will not take banking or engineering side.....some need only NLP some need CV experience
Thats sad. What is not said enough is how far apart data science positions can be. All called "Data Scientist" but your day to day duties are so different.
@@dominicj7977 thats what we are talking....one more certification..........and its not about certification.....even if we have, they need experience in banking sector.
I don't know what justifies you to say some of the things that you expressed in your video, but as a Data Scientist myself, I found the content you provided at the end of your video to be absolutely horrific advice. I can tell you that I have a specific set of technical skill sets I use and I do NOT defer from those skill sets. If I'm asked to solve a problem, I have the requisite skill sets to do that. However, if I were told or expected to work on some new technology or stack that was not aligned with my specialized skill set, I would NOT engage that project. You must be able to draw boundaries with companies what you can and won't do because if you don't, you will be exploited in a way that causes you to work >40 hour weeks. Don't get into that situation. I've resigned from jobs where the expectations did not match my technical skill sets or changed in some way from the onset of being hired for a DS job. Having said all off that, it should be noted that the technical skill sets I have should cover the better part of 90% of the work I will be doing in this space. However, do NOT just pick up and do anything that an employer barks out. That will put you in a very bad position in a short period of time.
Just bc your job doesnt align with what he is saying doesn't mean it's not happening 😂. There are plenty of data scientist, analyst, engineers thats agree with what he is saying. Most companies don't even correctly know what data scientist vs Data engineer is and think they do the same thing. Especially start ups (which a good chunk of data scientist and analysts are hired in). Often doing work not even theirs. Hell I worked a job that wanted me to do things software engineer did bc they were confused about the difference (i left eventually). Bc they don't know data analyst or what they do they set unrealistic goals for the person
@@TheJmoneyp You stated that you eventually left a company due to its expectations being misaligned with your skill sets. I think we agree. Not sure what your argument is here.
Yeah that's tech my man. I see a lot of people saying this constant refresh and learning isn't a bug but rather a feature. Yes, sure, definitely when you're in that mode. But life comes at you fast and at some point you need to set aside brain cycles for things other than code, algorithms and constant research. It's nice to be able to rely on a well-crafted skill at some point without continually updating. This gets at the real trap which is if you ever do get comfortable in any way, it's a false comfort that when you wake up from that world (age out, get fired, etc) that what you've been doing is relevant in any way.
Is there even any tech job that doesn't require you to constantly update your knowledge of the field you working on? For you to remain relevant in the market there is no way of escaping the continual learning phase you just have to embrace it and will go a long way in helping you.
Honestly I've been looking for directions, and I got it in this video. So many unanswered questions but your video are answering them. Thank you so much for taking your time to create this video, I'm grateful. Just started the journey too and I'm currently learning python. I just hope I'm starting out right.
You are welcome. I'm wishing you all the best in your learning journey. You can check out this video: th-cam.com/video/huoTWEhUaxU/w-d-xo.html where I shared how I learnt and got a job after 6 weeks.
First 2 points are very very true, i firmly agree with them. It is because of these shitty bootcamps and courses many people have started thinking AI jobs are easy and high paying but thats not true. You never get the sense of fullfillment here, always feels there is something pending. Sometimes you just do stuff hoping things will work and end up wasting time. I personally thing being an SDE in a top product based company is a lot better than being a Data Scientist/AI engineer.
Whether learning or not, data scientist or not, my goal is always how to get out of the rat race, which means how to save as much as possible as soon as possible such that you can get out and either do what you want to do or relax. Thanks for sharing your journey. As I grow older, I'm more excited Abt nearing retirement and/or death so I can leave this capitalistic world to the new gen 😅
Very True Im not so thrilled about dying yet, but Im definitely looking forward to retirement as soon as possible -I think there is so much you can do after retirement if you are prepared
Imagine being in my position. I started 2 years ago at the age of 48 starting from zero , playing catch up to to people like you, having to learn coding, data analytics, data engineering, data science, machine learning, llm's, lang chain, rag, agents, my brain is going to f@#$ing explode. once llms hit the scene I knew this was the point of no return and so here I am. embrace it.
I’ve been working in IT for over 30 years, and every 10 years the goal post change. You have to reboot in terms of learning. Fundamentals remain the same but something new always comes along. You need to have a passion for IT so you enjoy it and learning does not become a chore. That’s the nature of the beast. If you want to improve your chances of getting that “dream” job. The best way is to build something (this also accelerates learning) and showcase it at your interview. It demonstrates a multitude of skills: intelligence, presentation skills, coding, communication, and in-depth technical knowledge, to name a few. If you’re not building a side hustle project, then you most likely don’t have a passion. IT is vast so find the area that excites you the most and excel in it. There are no short cuts in becoming competent, competition is too great. With AI, this is literally the best and easiest time right now to learn anything, and it will only get better. You can’t pick IT as an industry just because you want to make big salary because your skill set will always need updating. You need to enjoy what you’re doing and you must embrace change.
you shares the real condition of this field. if competition increases then very hard to sustain at such places. we should have to always find out the less competitive fields where low supply and high demand. don't stuck anywhere just move on. change is the only constant in life
Role overlap and confusion between different teams is another big issue. If someone else is doing your role in a related team, the risk of getting pushed into work you weren’t hired for increases. Incredibly hard to push back, if you see it happening (and it can’t be resolved) then start applying elsewhere. For me, this meant moving cities, countries. Not sure other jobs are better though. Save, invest.
I think this does not apply to data scientists alone. Most jobs like project managers and business analysts are experiencing exactly all you mentioned. They always ask what balance of specialists and general skills the need to maintain.
My experience is rising complexity throughout the project because the data is never that simple and clearly structured as the client tells you in the first 1-2 meetings before you get access to it and their demands on the ML solution will grow as well as you tell them the details they didn't consider once you get insight to the data - making me soon after telling them my time estimation and salary becoming aware of my heavy underestimation.
You are spot on about what skills are needed to excel in a DS job. Its frustrating that most job adverts are 100% tech skills based. As a previous Head of DS what I cared about was attitude more than skills since being able to learn on the job, take the initiative etc were the most important factors in team success, not whether you knew pandas or pytorch off the top of your head (reason I hate most tech tests). Now I am out of a job and looking for a new one I am finding it difficult. Hiring managers care mostly about skills, not experience and I am only 42! I have made a list of courses I am going to do to keep up/refresh. Its never ending.
Those skills are impossible to prove. Take initiative. Yeah, sure. What exactly will you be doing when you don't know anything? What and how are you doing it? I've developed those skills after working on several smaller projects with some guidance. And now, a few years later, I can optimize, take initiative, etc. I wanted to do all that from day one, but realistically, it was impossible
That's how being in software engineering has always been. When Data Scientist is a programmer then it won't be a new thing because as a programmer, we always learn new things. Programming is not static so not statistical, to stay in tech, you need to always learn
The "secret" of long term success in tech (especially in areas of creation, design and development) is to be prepared to constantly train, stay up to date and be flexible in terms of areas of specialization. As you have clearly realized. 🙂🙂
My sad experience: I did the analysis of my life using a pipeline I setup from scratch, visuals were beautiful, deck was simple and clear, made code available, extra dashboards and tables available for whoever wanted to dive a bit deeper. No one gave a shit. Mind you, I had done the stakeholder management and had clear requirements which I met. They simply weren't willing to engage because it went beyond an average. Disappointing but also a good learning to always make sure if a little dashboard or table won't do.
Data Scientist is just a watered down version of a Statistician, but I guess Silicon valley wanted to get all the data jobs. Data engineering is an old IT role with a brand new name. Old whine in new bottles.
Guys adding more stuff to the arsenal is not that hard, takes 1-7 days to learn something new in the field because the foundation remains the same. Continuous self development is key in tech. Monotonous jobs creates anger, resentment and a feeling of failure. So to balance I say make sure not to make your life your job.
There's nothing wrong with being a data scientist. All these challenges are similar to other roles. This is corporate that we are talking about. That's why pursuing your postgraduate studies is important because that experience makes your life easier in corporate.
(1). Sometimes you will also need to read some crazy ground breaking research papers that are not easily replicable in the real world. (2). The compute for working with SOTA is not always adequate in most smaller and mid size companies. e.g Deploying a medium size LLM model internally will cost you a lot of money not to even talk of fine tuning them. (3.) Real world data is such a mess. Imaging working with images, XML, JSON and CSV data just for one service.
So I’ve been a DS for a while with a background in math. I’ve never had trouble picking up on new areas because it’s all based on math. You can study on the job. I learned about LLMs during work hours; I never work after my job and stick to the 9-5. I wouldn’t worry too much about reading the latest papers. But yeah, agree with unrealistic expectations. I spend more time talking than coding at this point
Is there actually enough data every day to able to create and analyze the data to make this a viable job everyday from 9 to 5? I jsut don't understand how there can be so much data to be analyzed. The work of data analyst seems to be something suited for freelancing for a while but not soemthing like a consistent work.
@@batman-sr2px , you will never be doing coding 9-5. It's mainly meetings, speaking with stakeholders, then coding. And paperwork. There's a ton of data out there, that's never a problem
@@acatisgreat11111ff thanks. Also only except work from home opportunity if the job listing said so or are they flexible enough to give some days after you got the job and it didn't say so? How many job listing would you say are either WFH or only office is it about like 50/50?
It's disappointing how trivial and tedious so much of the work can be. Like you say, Excel ends up dominating in a corporate environment. Stuff that should be done in Python ends up in excel because managers are too low IQ to use Python. If you're getting paid well it can be worthwhile to stick it out in one of these jobs, but better invest wisely so you don't have to do it deep into middle age.
@@justinian420 1. Thanks so its converted into excel later for the managers to view and that goes pretty smooth or tedious? 2. Are job listings pretty split even between WFH and office only positions? Do you find jobs to be pretty flexible to allows WFH days if never mentioned in the job listing?
I have a have a back ground in communication, and i want to divert and get some tech skills. Which would you advice as a beginner Data Science or Data Analyst?
This doesn’t really sound like Data Science but more like Data Engineering. Data Science is primarily research focused. Most big techs data scientists are mostly research scientists
I took a paid boot camp and ran it for almost 6months. Afterwards was 3 weeks of Internship, but i got a job offer in an engineering firm, throughout this almost 7 months, i was still learning and learning that long without no pay or result is just not going to fly especially if youre under your parent roof. I took the job, tried running both carrers, eventually had to let DS go but still I watch your videos to keep myself farmiliar with the field.
This also happened to me, I had to stop learning data science to find something that would be bringing in money. But I'm now back to learning data science.
Creating new labels for the field of work. Data scientists… data drive , you crunch the numbers into a diagram for a lazy manager… good luck for you job security. Redundant at best.
(1) Sad : The only thing that can be actually SAD about Data Scientists is if their role (DS) were to become REDUNDANT. (2) Competition : What has been referred to as 'competition' are actually the same folks who share your 'interests': those who understand your curiosities-&-likes that others don't get. (3) Dark-Side : Anything but destroying human-life, communities, or the HOME-planet is actually much on the BRIGHT-side.
Data science is super boring. I feel the pain of my co-worker sitting next to me when she has to wait 4hrs to train a model only to realize that the accuracy is unacceptable and then start the re-training again. Dosen't look like too many things can be done at the same time. For the learning complaint, this is general in most IT fields.
Using terms like 'data scientist' doesn't really help; the majority of IT bods can't even integrate/differentiate. Learn a real discipline, and then move onto IT if that is what you want to do.
Hello Samson, I'm Selassy from Ghana and would like to seek your professional advice. I want to join the military in my country but as a data scientist. I have no knowledge in computer science or data science. How do I go about my journey. Also, how is data scientist relevant to modern day's military
For the latter, I can't speak authoritatively about that. However, for the earlier, You can check out my guide here: th-cam.com/video/huoTWEhUaxU/w-d-xo.html
you get tired of learning?...oh no..something must be wrong with me cuz i never ever get tired of learning..ever..i read everything from science to cook books..i love to learn new things
For unrealistic expectations, is that something that every DS will face as part of their job? or... is it normally handled by leader such as Lead DS or Principal DS?
For me, My Previous Team lead was responsible for setting things straight. Now, that I lead a Team, I do that. It's just important to know and be ready to put things correctly.
@@samson_afolabi I see. good advice. You're such a supportive leader. In my career as engineer, my leaders and managers usually don't want to get involve in this so engineers have to deal with unrealistic expectations by themselves. This is in Asia btw.
What I experienced and heard. A lot of companies do not understand what data analyst, data scientist are and do. Most data techies get hired at start ups. Since most ppl don't understand data they think...ah this guy is a data guy this guy knows everything and will solve all my problems. Give you loads of things that aren't even in your field like software engineer or marketing projects campaign😂.
@@TheJmoneyp i'm not in data field, but i did hear similar story multiple times from events, where people were hired as data scientist, after joined the company then only found out the org misunderstood what data science is all about, setting up data science team with wrong expectation.
Please I need your help I studied accounting but i am interested in learning data science, I have been trying to learn data science on TH-cam, but the funny thing is that I don’t know where to start from
I guess the reason why he said No, is about a structure and planning. That’s why I recommend some of this online platforms like DataQuest or Data camp. They can help get you started. You can check out my video on how I got started here - th-cam.com/video/huoTWEhUaxU/w-d-xo.htmlsi=JNgew40mXHFKl7JQ
Hi guys,
Thanks for watching. I would love to hear from you, what are the sad realities you’ve experienced as a Data Scientist.
Don’t Forget to like and Subscribe.😊
THank you for giving me insight on this troubling issue. This video reaLly helped 👍 😄
Bro getting job as a fresher is difficult in ds
So I decided to for data analytics gain some ex than jump into ds.but the thing I don't like visualization part .like tableau but rather only interested in ml,dl, part
So should I still go for da or other tech gain some ex and then jump into ds?
Great video, best advice is asking the right people the right questions and not getting sidetracked
Sir,do you train?
I just got on your video and is really helpful.
Please can you mentor Me?
To be honest, when you work in tech, you must have the mindset to always want to learn. That's just how things are in the field of Computer Science.
Definitely !!!! It is a constant change and evolution if not be an accountant (no offense to accountants 😅)
or find a job where you use Java as backend... in old banks etc.. there's always an alternative :)
@@rigobertoitachijohnsonJAVA = 🤡
The sad thing is, most of the "knowledge" becomes obsolete in a few years.
@@johnnyq4260 yeah things are moving too fast. 6 months and what you read is useless lol
1. If you didn’t plan to always be learning, you’ve chosen the wrong field.
2. Unless you’re in an extremely mature organization with highly segmented labor, you will almost certainly have to play the role of facilitator. If you want to be a staff or principal level researcher, you absolutely must do this anywhere.
3. Following 2, nobody cares about your tech skills, they care about the value you produce.
4. Your real job is to create order out of ambiguity.
5. If you’re good at what you do, the market is ripe with opportunity right now. If you don’t have experience, it’s brutal.
😢
How can you have experience, if companies don't give you an opportunity to have experience? 😂
@@enjoyourjoint5012 Try to do data analyst or data science projects in your current jobs. Try to get your hands on data, excel, csv files etc, then do a project. If there's no data, try to think of some trends or analysis that would be useful. This will give you hands on experience and you can put it on your CV.
Any advice for total newbies?
@@enjoyourjoint5012 become an Intern, basically an unpaid employee? I don't know either
people that look forward to studying and learning about new things during non-work hours are the most natural fit for tech fields.
And they work this 12 hours a day and are under stress
All high paying jobs are this way. There’s nowhere to run. Constant learning, unreasonable expectations.
The problem is there aren't any not-so-high paying jobs either
So what courses do you suggest we should do?@@bigdreams5554
What's wrong with constantly learning and challenging yourself? I I agree with unreasonable expectations, which no one wants to do. But if you're not constantly learning and challenging yourself or don't want to, then you're in the wrong field of work. If you're only in for the money, which, nothing wrong with that, then find a simpler career. Going into computer science and not challenging yourself to learn more or stay update with technologies means you're behind and probably that guy getting put on the chopping block when it's time for layoffs.
GPT says no
it is supply and demand. once everyone can do it, it is no longer high paying.
The best approach is to follow the TH-camrs who specialize in the tools you choose. So as you regularly watch their videos, you are indirectly being updated on tech as well.
Can you please recommend me one of those.
As a current data scientist, I agree with everything you’ve said but also with a few comments as well. Tech in general we are expected to constantly learn/upskill and that can get tiring after many years
its the always and forever learning and adding skills that is the most difficult part i found out about . This is not how i imagine my future to be like when i was 20 and starting in the field . I wonder if anyone feels soulless at times
This is why I want to get out of tech. Being on the training treadmill is tiring. I understand that every career needs Continuous learning, but tech is a different level of upskilling, and it gives me anxiety.
I left the field after 30 years. The field is much different now. Ultimately, I was working 6 or 7 days a week. I couldn't take it anymore. It became unhealthy in many ways.
@@jegathingsbelieve me when I say there are days I stay up just to finish a project. Tech and especially in the field of data science, most people don’t understand how tiring working on a project is, they expect results in few days which is impossible. I love data science but people who don’t understand is what’s getting me on my nerves. It’s different than other fields.
@@jegathingsI used to work 15 hours a day not in tech field but in restaurant worst job
Software engineer turned data engineer eyeballing data science and this was helpful. Honestly I feel the same now with the overwhelming amount of tools and knowledge needed but it’s hard to complain when it feels more doable than say mechanical or electrical engineering. Anyone else feel this? Not imposter syndrome just honestly. It’s hard work and very demanding. Just different than other disciplines. Anyways I’m kind of bored of constantly learning a new tool every month or so. So I’m focusing on mastering things I enjoy and screw the employers and even other competition. Not worth my health. Gotta be smarter not work harder right!
It is crazy.
I am a trained data scientist, but I build ETL pipelines, dashboards, some software engineering commitments all the while working on my communication skills.
It is a lot to do, and while I am not really bothered by having a lot of work, the pay is ridiculous! I am highly underpaid and it is frustrating!
Keep persevering and I hope you get into your desired position very soon🤞
Sad to hear. But hang in there, I'm sure something better will come around soon.
Thanks for the video. I agree so called ‘soft skills’ such as communication are vital and often just as important as technical skills
First time here, am also a Data Scientist. I currently work as an instructor at a computer school teaching data courses. One of the lessons i picked from this video is that as a Data Scientist, u have to keep learning and its true. Sometimes, i feel as if am not trying. Thanks for making this video
I find your advice to be equally applicable to my role as an Excel specialist. There's no end to the learning, which is a positive for me. The most important skill, assuming one has the fundamental technical skills, is people management. Managing expectations will get you further than technical expertise...
is an excel specialist formally a data analyst or what? any tips on how to manage expectations?
Continuous learning is a prerequisite for nearly every career realm where high-value assets contribute. I’ve squandered countless hours down the rabbit hole in overhyped courses with clueless facilitators just rehashing definitions without any real-world applicable examples. It’s refreshing to hear someone tell the truth. 👍🏾
* I’ve squandered countless hours down* , Chile ! we all did and regrets are piling up lol!
This is the best explanation of what a data scientist does and whether it is worth doing at all.
I found your clear explanation incredibly inspiring. It motivated me today as I continue my journey in data science and machine learning engineering. Thanks so much sir
I studied Data Science in 2014 and got a job in 2015. I worked for a year and quit because of too many demands and I saw that in the future there will be less job. It was a good decision I made then. Nowadays it is better to be data engineering and upskill yourself and follow the job marketing trends.
You still have to keep learning in data engineering
But Data Science offers higher salary packages than Data Engineering?
Also, how are you saying there will be less job in future?
@@rameeziqbal8711because of AI
@@rameeziqbal8711 the pay is in the same ballpark
@@rameeziqbal8711AI is taking the place of many job roles.
'Always learning' is a good thing. Opens new possibilities.
Yep vital to stay employable in this day and age
The always learning part is what is unpaid and you gotta do on your own time, compare that to other job roles that pay just as well where you're not required to learn new stuff.
Essentially you're learning new things as your older skill becomes worthless.
@@dallysinghson5569 then you're in the wrong field of work if that's so troublesome to do. You may not be getting paid, but you're growing yourself and opening doors.
Depends on whether you or your partner expect you to have any free time for yourself or them
@@dallysinghson5569 In saying this, I do not mean to know more or better than you. Like your view, this is just another perspective. It is a sigh of relief that new techniques, new stacks, etc. are periodically released. It is true that they add work & challenges, but they are a constructive kind of work. We could get accustomed to kicking the butt of the same video game, playing it over, & over, & over. Fortunately, other devs are cooking up yet other video games to alter the look & play of existing ones. Loosely putting it, essentially, all video games are one & the same, reshuffled, reconfigured, resized, reimagined. We appreciate the classics while we also anticipate the new worlds that new games unfurl.
Highly relatable.. It's need a lot to be data scientist. Continuous learning is needed and unrealistic expectations is a real thing..
"Seeking is the Reward" -- you have to learn constantly in pretty much any field, CS included.
The key is having the appropriate degree and understanding the theoretical underpinnings of data science. If someone graduated from a boot camp, then they are at the mercy of learning tools or the technology and this is never a position you want to put yourself. If you’re truly serious about being a data scientist, you should have at least bachelors degree in applied statistics or something similar and better a masters degree, once you learn technique and the theoretical underpinnings of the discipline then you become much more resistant to change and it is much quicker to pick up new technologies because you understand how they inherently work .
Constant learning I find as an advantage, at least it's interesting.
I am starting a new job as a data reporting analyst and I'm super excited about it!
Congratulations 😁
Did you get your data analyst course from a boot camp or university or college?
Great video! Commenting so that it reaches people about to start out it data science and aren’t being told how competitive and challenging it is
Haha landing a role as a data scientist is super challenging! And you always have to keep improving. On top of that if you want to get promoted you have to not only be the most technical person in the room but also one of the most business savvy. Man on man is it a hard role to fill! But that’s why everyone wants to become one, because it’s a role that gives you purpose and pays well
seriously i started hating my job as a data scientist!! companies bucket list is increasing like hell. Trying to change my company but not a single profile matches mine.....they need almost 90% match.banking sector will not take engineering data scientist. Healh sector will not take banking or engineering side.....some need only NLP some need CV experience
Thats sad.
What is not said enough is how far apart data science positions can be. All called "Data Scientist" but your day to day duties are so different.
banks do hire non banking DS. You might need to get some banking related certifications
@@dominicj7977 thats what we are talking....one more certification..........and its not about certification.....even if we have, they need experience in banking sector.
honestly, spend three months writing your own blog, they will come chasing you. Recruiters are lazy AF. Use the top ten banks as case studies.
I don't know what justifies you to say some of the things that you expressed in your video, but as a Data Scientist myself, I found the content you provided at the end of your video to be absolutely horrific advice. I can tell you that I have a specific set of technical skill sets I use and I do NOT defer from those skill sets. If I'm asked to solve a problem, I have the requisite skill sets to do that. However, if I were told or expected to work on some new technology or stack that was not aligned with my specialized skill set, I would NOT engage that project. You must be able to draw boundaries with companies what you can and won't do because if you don't, you will be exploited in a way that causes you to work >40 hour weeks. Don't get into that situation. I've resigned from jobs where the expectations did not match my technical skill sets or changed in some way from the onset of being hired for a DS job. Having said all off that, it should be noted that the technical skill sets I have should cover the better part of 90% of the work I will be doing in this space. However, do NOT just pick up and do anything that an employer barks out. That will put you in a very bad position in a short period of time.
Ok
Yeah just shout "I don't want, I don't know"
Just bc your job doesnt align with what he is saying doesn't mean it's not happening 😂. There are plenty of data scientist, analyst, engineers thats agree with what he is saying. Most companies don't even correctly know what data scientist vs Data engineer is and think they do the same thing. Especially start ups (which a good chunk of data scientist and analysts are hired in). Often doing work not even theirs. Hell I worked a job that wanted me to do things software engineer did bc they were confused about the difference (i left eventually). Bc they don't know data analyst or what they do they set unrealistic goals for the person
@@TheJmoneyp You stated that you eventually left a company due to its expectations being misaligned with your skill sets. I think we agree. Not sure what your argument is here.
Yeah that's tech my man. I see a lot of people saying this constant refresh and learning isn't a bug but rather a feature. Yes, sure, definitely when you're in that mode. But life comes at you fast and at some point you need to set aside brain cycles for things other than code, algorithms and constant research. It's nice to be able to rely on a well-crafted skill at some point without continually updating. This gets at the real trap which is if you ever do get comfortable in any way, it's a false comfort that when you wake up from that world (age out, get fired, etc) that what you've been doing is relevant in any way.
Is there even any tech job that doesn't require you to constantly update your knowledge of the field you working on? For you to remain relevant in the market there is no way of escaping the continual learning phase you just have to embrace it and will go a long way in helping you.
Honestly I've been looking for directions, and I got it in this video.
So many unanswered questions but your video are answering them. Thank you so much for taking your time to create this video, I'm grateful.
Just started the journey too and I'm currently learning python. I just hope I'm starting out right.
You are welcome.
I'm wishing you all the best in your learning journey. You can check out this video: th-cam.com/video/huoTWEhUaxU/w-d-xo.html where I shared how I learnt and got a job after 6 weeks.
I’m starting on Monday, are you learning yourself or going through a school?
Fine video. I appreciate the honesty. You seem like a nice and smart guy. Best of luck.
First 2 points are very very true, i firmly agree with them. It is because of these shitty bootcamps and courses many people have started thinking AI jobs are easy and high paying but thats not true. You never get the sense of fullfillment here, always feels there is something pending. Sometimes you just do stuff hoping things will work and end up wasting time. I personally thing being an SDE in a top product based company is a lot better than being a Data Scientist/AI engineer.
What’s SDE
Whether learning or not, data scientist or not, my goal is always how to get out of the rat race, which means how to save as much as possible as soon as possible such that you can get out and either do what you want to do or relax. Thanks for sharing your journey. As I grow older, I'm more excited Abt nearing retirement and/or death so I can leave this capitalistic world to the new gen 😅
You are exactly my kind of person.
Very True Im not so thrilled about dying yet, but Im definitely looking forward to retirement as soon as possible -I think there is so much you can do after retirement if you are prepared
Imagine being in my position. I started 2 years ago at the age of 48 starting from zero , playing catch up to to people like you, having to learn coding, data analytics, data engineering, data science, machine learning, llm's, lang chain, rag, agents, my brain is going to f@#$ing explode. once llms hit the scene I knew this was the point of no return and so here I am. embrace it.
Kudos for being able to learn these things at your age. How did u learn them? Coursera? I have a 17 yo getting into data science/ml.
I’ve been working in IT for over 30 years, and every 10 years the goal post change. You have to reboot in terms of learning. Fundamentals remain the same but something new always comes along. You need to have a passion for IT so you enjoy it and learning does not become a chore. That’s the nature of the beast.
If you want to improve your chances of getting that “dream” job. The best way is to build something (this also accelerates learning) and showcase it at your interview. It demonstrates a multitude of skills: intelligence, presentation skills, coding, communication, and in-depth technical knowledge, to name a few. If you’re not building a side hustle project, then you most likely don’t have a passion. IT is vast so find the area that excites you the most and excel in it. There are no short cuts in becoming competent, competition is too great.
With AI, this is literally the best and easiest time right now to learn anything, and it will only get better. You can’t pick IT as an industry just because you want to make big salary because your skill set will always need updating. You need to enjoy what you’re doing and you must embrace change.
you shares the real condition of this field. if competition increases then very hard to sustain at such places. we should have to always find out the less competitive fields where low supply and high demand. don't stuck anywhere just move on. change is the only constant in life
Wow!
Thus is the first TH-cam video I've watched that literally breaks down what data scientist do exactly.
Thanks so much
Role overlap and confusion between different teams is another big issue. If someone else is doing your role in a related team, the risk of getting pushed into work you weren’t hired for increases. Incredibly hard to push back, if you see it happening (and it can’t be resolved) then start applying elsewhere. For me, this meant moving cities, countries. Not sure other jobs are better though. Save, invest.
I think this does not apply to data scientists alone. Most jobs like project managers and business analysts are experiencing exactly all you mentioned. They always ask what balance of specialists and general skills the need to maintain.
Interesting, I guess its everywhere.
but is that listed in the job role or kind of just thrown on the fly to you?
My experience is rising complexity throughout the project because the data is never that simple and clearly structured as the client tells you in the first 1-2 meetings before you get access to it and their demands on the ML solution will grow as well as you tell them the details they didn't consider once you get insight to the data - making me soon after telling them my time estimation and salary becoming aware of my heavy underestimation.
Thanks.. These look like the issues in every high learning professionals
You are spot on about what skills are needed to excel in a DS job. Its frustrating that most job adverts are 100% tech skills based. As a previous Head of DS what I cared about was attitude more than skills since being able to learn on the job, take the initiative etc were the most important factors in team success, not whether you knew pandas or pytorch off the top of your head (reason I hate most tech tests). Now I am out of a job and looking for a new one I am finding it difficult. Hiring managers care mostly about skills, not experience and I am only 42! I have made a list of courses I am going to do to keep up/refresh. Its never ending.
Those skills are impossible to prove. Take initiative. Yeah, sure. What exactly will you be doing when you don't know anything? What and how are you doing it? I've developed those skills after working on several smaller projects with some guidance. And now, a few years later, I can optimize, take initiative, etc. I wanted to do all that from day one, but realistically, it was impossible
That's how being in software engineering has always been. When Data Scientist is a programmer then it won't be a new thing because as a programmer, we always learn new things. Programming is not static so not statistical, to stay in tech, you need to always learn
The "secret" of long term success in tech (especially in areas of creation, design and development) is to be prepared to constantly train, stay up to date and be flexible in terms of areas of specialization. As you have clearly realized. 🙂🙂
Thank you so much for the enlightenment
My sad experience: I did the analysis of my life using a pipeline I setup from scratch, visuals were beautiful, deck was simple and clear, made code available, extra dashboards and tables available for whoever wanted to dive a bit deeper. No one gave a shit. Mind you, I had done the stakeholder management and had clear requirements which I met. They simply weren't willing to engage because it went beyond an average. Disappointing but also a good learning to always make sure if a little dashboard or table won't do.
I give a shit! Would love to see more of this do you have a link?
@@nintendowiirulz You are too kind. It's company property I'm afraid so can't share.
@@vlemvlemvlem3659 ahh no worries
So sad to hear.
What you've described is the sad realities of software development. No matter the discipline. Because of that, you gotta Like out of me.
It is indeed a demanding journey... however your employer should/must support your constant learning process... for a mutual benefit.
Welcome to data engineering. The much more needed profession. Way cooler technologies like kafka spark and much more.
Data Scientist is just a watered down version of a Statistician, but I guess Silicon valley wanted to get all the data jobs. Data engineering is an old IT role with a brand new name. Old whine in new bottles.
I am a mech engineer and i am always learning say every new problem is a new challenge
Guys adding more stuff to the arsenal is not that hard, takes 1-7 days to learn something new in the field because the foundation remains the same. Continuous self development is key in tech. Monotonous jobs creates anger, resentment and a feeling of failure. So to balance I say make sure not to make your life your job.
Not true. Tools are introducing new levels of abstraction that make the basic useless.
Finally someone speaks the reality of things.
There's nothing wrong with being a data scientist. All these challenges are similar to other roles. This is corporate that we are talking about. That's why pursuing your postgraduate studies is important because that experience makes your life easier in corporate.
(1). Sometimes you will also need to read some crazy ground breaking research papers that are not easily replicable in the real world.
(2). The compute for working with SOTA is not always adequate in most smaller and mid size companies. e.g Deploying a medium size LLM model internally will cost you a lot of money not to even talk of fine tuning them.
(3.) Real world data is such a mess. Imaging working with images, XML, JSON and CSV data just for one service.
The majority of those 100 applicant have no idea of what data science involves
They won't until you give them a chance.... And some of them might not see this as a problem
If you can't communicate your findings to non-data oriented colleagues, you have absolutely no business being a DA or DS
Thank you for this
Thanks for your advice
So I’ve been a DS for a while with a background in math. I’ve never had trouble picking up on new areas because it’s all based on math.
You can study on the job. I learned about LLMs during work hours; I never work after my job and stick to the 9-5. I wouldn’t worry too much about reading the latest papers.
But yeah, agree with unrealistic expectations. I spend more time talking than coding at this point
Is there actually enough data every day to able to create and analyze the data to make this a viable job everyday from 9 to 5? I jsut don't understand how there can be so much data to be analyzed. The work of data analyst seems to be something suited for freelancing for a while but not soemthing like a consistent work.
@@batman-sr2px , you will never be doing coding 9-5. It's mainly meetings, speaking with stakeholders, then coding. And paperwork. There's a ton of data out there, that's never a problem
@@acatisgreat11111ff thanks. Also only except work from home opportunity if the job listing said so or are they flexible enough to give some days after you got the job and it didn't say so? How many job listing would you say are either WFH or only office is it about like 50/50?
No 2 is the realest response
It's disappointing how trivial and tedious so much of the work can be. Like you say, Excel ends up dominating in a corporate environment. Stuff that should be done in Python ends up in excel because managers are too low IQ to use Python. If you're getting paid well it can be worthwhile to stick it out in one of these jobs, but better invest wisely so you don't have to do it deep into middle age.
Typically expect all managers to not know how to use python right? Do you have to do the tasks in excel or you do them in python then convert?
@@batman-sr2px typically I do as much as I can in Python
@@justinian420 1. Thanks so its converted into excel later for the managers to view and that goes pretty smooth or tedious? 2. Are job listings pretty split even between WFH and office only positions? Do you find jobs to be pretty flexible to allows WFH days if never mentioned in the job listing?
Totally unreal expectations from business people. And all they care about are LLM this and that when traditional ML could be much more fruitful
I have a have a back ground in communication, and i want to divert and get some tech skills. Which would you advice as a beginner Data Science or Data Analyst?
This doesn’t really sound like Data Science but more like Data Engineering. Data Science is primarily research focused. Most big techs data scientists are mostly research scientists
I took a paid boot camp and ran it for almost 6months. Afterwards was 3 weeks of Internship, but i got a job offer in an engineering firm, throughout this almost 7 months, i was still learning and learning that long without no pay or result is just not going to fly especially if youre under your parent roof. I took the job, tried running both carrers, eventually had to let DS go but still I watch your videos to keep myself farmiliar with the field.
This also happened to me, I had to stop learning data science to find something that would be bringing in money. But I'm now back to learning data science.
What app did your screen recording??
I like ❤
Very informative 👏🏽👏🏽👏🏽🔥
There are Challenges in Every Profession...
Great content.
When people are rushing into anything data, AI will soon take over this soon.
Creating new labels for the field of work. Data scientists… data drive , you crunch the numbers into a diagram for a lazy manager… good luck for you job security. Redundant at best.
Interesting perspective!
(1) Sad : The only thing that can be actually SAD about Data Scientists is if their role (DS) were to become REDUNDANT.
(2) Competition : What has been referred to as 'competition' are actually the same folks who share your 'interests': those who understand your curiosities-&-likes that others don't get.
(3) Dark-Side : Anything but destroying human-life, communities, or the HOME-planet is actually much on the BRIGHT-side.
Data science is super boring. I feel the pain of my co-worker sitting next to me when she has to wait 4hrs to train a model only to realize that the accuracy is unacceptable and then start the re-training again. Dosen't look like too many things can be done at the same time. For the learning complaint, this is general in most IT fields.
Continuous LEARNING is implicit if you are in the tech field.
This just sounds like any software engineering field. If career learning isn’t for you then don’t even start a tech career. It is life in tech
thanks man!
Using terms like 'data scientist' doesn't really help; the majority of IT bods can't even integrate/differentiate. Learn a real discipline, and then move onto IT if that is what you want to do.
Hello Samson,
I'm Selassy from Ghana and would like to seek your professional advice. I want to join the military in my country but as a data scientist. I have no knowledge in computer science or data science. How do I go about my journey. Also, how is data scientist relevant to modern day's military
For the latter, I can't speak authoritatively about that.
However, for the earlier, You can check out my guide here: th-cam.com/video/huoTWEhUaxU/w-d-xo.html
What other jobs that are high paying where you don’t have to keep learning?
sounds like you're explaining why your job was difficult
I can relate with the magician thing 🤣🤣🤣
you get tired of learning?...oh no..something must be wrong with me cuz i never ever get tired of learning..ever..i read everything from science to cook books..i love to learn new things
This is me too, I read everything. I watch every kind of content.
But why is learning a harsh or sad reality..I like researching and learning so that is not sad at all😂😂😂😂
Did you really quit or are you still practicing DS?
“Magician 🎩🔮👳🏾♂️🪄🧙🏽” lol 😂
I want to join the military but as a data scientist
Trying looking for defense contractors instead.
Thanks for this explanation, please how can I connect with you?
www.linkedin.com/in/samson-afolabi/
If you stop now you will be behind forever it's so much happening now
Data science is easy, just shit out nonsense and hide behind a phd and hype
@sunnohh Since your such an expert, try shitting out bricks …made of lead …. by the ton my friend.😂
I'm new into tech like beginner beginner and about to get a laptop 🥱 please, should i proceed or not?
Proceed please. It'll worth it if you're consistent
Hey sir,
Is it advisable study Msc data science in Germany
For unrealistic expectations, is that something that every DS will face as part of their job? or... is it normally handled by leader such as Lead DS or Principal DS?
For me,
My Previous Team lead was responsible for setting things straight. Now, that I lead a Team, I do that. It's just important to know and be ready to put things correctly.
@@samson_afolabi I see. good advice. You're such a supportive leader. In my career as engineer, my leaders and managers usually don't want to get involve in this so engineers have to deal with unrealistic expectations by themselves. This is in Asia btw.
What I experienced and heard. A lot of companies do not understand what data analyst, data scientist are and do. Most data techies get hired at start ups. Since most ppl don't understand data they think...ah this guy is a data guy this guy knows everything and will solve all my problems. Give you loads of things that aren't even in your field like software engineer or marketing projects campaign😂.
@@TheJmoneyp i'm not in data field, but i did hear similar story multiple times from events, where people were hired as data scientist, after joined the company then only found out the org misunderstood what data science is all about, setting up data science team with wrong expectation.
Please I need your help
I studied accounting but i am interested in learning data science, I have been trying to learn data science on TH-cam, but the funny thing is that I don’t know where to start from
don't do it
@@93hothead please why
I guess the reason why he said No, is about a structure and planning. That’s why I recommend some of this online platforms like DataQuest or Data camp. They can help get you started. You can check out my video on how I got started here - th-cam.com/video/huoTWEhUaxU/w-d-xo.htmlsi=JNgew40mXHFKl7JQ
@@samson_afolabi thank you so much
Personally i dont think any of these are sad actually. Its just the job market
Let’s Gooo 🔥
i wonder if its even a good field to get into becuase of the rise of AI and such
Weldone
Actually All tech jobs have the same sad realities.
Does "Data Scientist" means you are a scientist who study data? Isnt this boring?
Maybe maybe not.
Data is cool - lots of things to learn from data
yeah, that's what a data scientist does. It can also be magical
The market ain't stable
omo na you sabi
lol…this got me laughing 😄