The Harsh Reality of Being a Data Scientist

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Data Scientist is a great role to be in but it comes with its cons. In this video, we are discussing the unglamorous side of data science. Did any of the things mentioned resonate with your experience?
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I'm Sundas. I'm a self-taught data scientist from a non-tech background, currently at a FAANG company. I have been in the industry for over 8 years spread across two big tech companies. On this channel, I share tips for people interested in entering data science with the goal to democratize knowledge and make complicated topics digestible for everyone. All opinions are mine!
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@123arskas Год назад

I'm learning Data Science and whenever I read job descriptions for entry levels or even for Interns they want you to be jack of all trades and on top of that require you to have 2,3 years of experience. Plus they include big data streamlines and ask you to be an expert on it too along with all sorts of cloud services. I mean it feels like they're demanding an Intermediate Data Scientist and terming it as "Data Analysis Intern" or "Junior Data Analyst" role. This frustrates me a lot.

@raxosc1475 Год назад

Me too. I feel you 😢

@raxosc1475 Год назад

@@weinjien5436 do you think that would be enough? I need to make one of those courses.

@weinjien5436 Год назад

@Raxosc 14 online course will be very helpful to prove ur skill sets (given that you dont have any experience)

@123arskas Год назад

@@weinjien5436 For a minute there I thought you said "14" online courses. As for me I know GCP basics.

@raxosc1475 Год назад

@@123arskas 🤣🤣🤣🤣

@ricklewis4442 Год назад

I love being a Data Scientist and have never had a better job. To me the job of a Data Scientist is to translate a business problem into a math problem which can be solved with the available data. Solving it is the easy part. To do this, we are part business analyst, part financial analyst, part data engineer, part software developer, part machine learning engineer, part statistician, part visualization engineer and part product manager. The ambiguity is off the chart and the need to learn is constant. When I hire, I look for determination, intellectual curiosity, desire to constantly learn as well as the ability to deal with ambiguity and failure. The hard skills I can teach.

@minutemud1938 Год назад

Hello Rick, it's an interesting job based on your explanation. I work as a logistic business analyst and I've been trying to switch to data science and really need a good mentor to set my mindset in place. Could we connect? I'm really looking forward to hear your feedback 🙏🏻

@analyticalmindset Год назад

To me y'all are half statistician and half analyst. From the outside looking in as a data analyst.

@cemkalender4026 Год назад

You're no data engineer.

@chibuikemefugha3277 10 месяцев назад

I love this comment. As a data scientist, curiosity, enthusiasm is the key. For me 2 years now freelancing in the field and I know how it feels. Another important part, you must be a team player and in most cases have a good managerial skill in order to advance in the career. I wish I get the opportunity to work with you someday.

@kavy0111 5 месяцев назад

Hey is masters important for this job role if you wanna get into big companies and mncs? Or should I just complete my undergrad?

@Karenshow Год назад

In my personal experience the harsh reality also included: 1. Studying all the time, to the point that you personal life gets affected. 8 hours of work and 4 hours a day of just keep up with the new lake, cloud , software, technique, library , bi tool etc. 2. The feeling of "You don't know enough", "You are not enough". You briefly mention this and I am glad that I am not the only feeling the same way. I know python enough to do my job, but I am not a python expert who can write functions from scratch, or change between languages say from python to java or R. I use the existing libraries and move on to the next project.

@_truthful_q_ Год назад

My question is, would you do this kinda thing if you weren't getting paid?

@MemoContrerasf Год назад

You don’t need to keep up with the new stuff. It’s not like companies have unlimited money to switch cloud when a product releases. Or change a whole working thing because this bi tool is cool. Tf you work

@ricklewis4442 Год назад

This is exactly why I love being a Data Science... I'm always learning and it never gets boring.

@prateekbhardwaj9943 Год назад

same i feel as full stack developer

@eddiedantes7732 Год назад

Build foundation. If you understand the basic concepts of object oriented programming, basic computation, os (unix based kernels), then keeping up with trends isn't all that difficult. Technologies, libraries, frameworks, etc. are an abstraction of the fundamentals. You'll never "know" enough. It's not about knowing. It's about collaboration, researching the issue, and gathering the best tools to solve the problem.

@nsnishantsaini5439 Год назад

Its really difficult to work as a Data scientist because every company have different expections from Data Scientist. And now a days, a data scientist should know all the skills like computer vision, deep learning, Operational research, Machine learning, SQL and many more. There must a discrete line between data scientist work roles. And also as you have mentioned interview prep, it is really difficult because we need to prep from scratch. - Struggle of a DataScientist

@OMPRAKASH-tl6yc Год назад

But many online institutes provide training saying anyone can be data scientist and get placement too.. with good CTC of minimum 7 L is that true, Do any one transist this career in Data scientist ? Is good option ?

@kaydeeem3961 Год назад

I agree with the part about the necessity of being versatile. Of course, looking for a job, one can just ignore the job offers containing techs one does not know. But in my view, there are so many of them that after that 'offer elimination' process, one's final list could turn out to be pretty short. Right now, I work as a Mid Data Scientist, and although I feel confident in what I am doing on a daily basis, I have (and constantly update) my 'to learn' list.

@FriendsforFriendsUK Год назад

I don't know whether to laugh or cry when you say you are expected to know Operational research as well as the other stuff. Operational Research is huge (not just optimisation). It certainly requires data analysis and statistics skills - and SQL and communications and modelling and data cleaning..... I found that people are in awe of the trivial stuff that they can almost understand (e.g. spreadsheets with actual formulae!) and the challenging stuff is so far over their heads they don't even realise it is needed or even that it is there. I can relate to Sundas Khalid when I think of managers I had who really did not appreciate what the discipline offers. I had to do the stuff they asked for while trying to slip in the stuff that I knew would be useful. Now I can see that the same applies to related topics such as Data Science.

@analyticalmindset Год назад

Ok I thought I was crazy feeling like I had to learn financial risk modeling from scratch before my interview and do a little quick project to show my ability lol This being for a Quant risk analyst role at a bank

@roomaparveen306 Год назад

@@OMPRAKASH-tl6yc hi

@patriciam6184 Год назад

Great insight! I got into data science right after college and really struggled to do so. The fact that the data science job role is defined so differently at different companies made interviews really hard to prep for. It felt like you need to be a jack of all trades and be well versed in data science, data engineering and data analyst principles and it was just a lot to prep for. Plus a lot of roles require graduate degrees. After I got a role, I left after a year and transitioned into SWE as like you said the expectations didn’t match the reality plus I was also at a toxic workplace. I realized that I want to be in a role that is more well-defined and somewhat uniform across companies so if i need to look for a job later, I’m not being restricted to only a subset of opportunities bc of the different definitions and requirements.

@Arbi_kureshi Год назад

Hey! I am actually trying really hard to get into data science but there are a few complications that i am facing and I don’t have a degree in this field, i spoke with a few counsellors as well but they couldn’t provide me with the answers that i was looking for, in the end I believe someone who is already in this field can help me out with my queries, so i was hoping if you could like help me a little on a few concepts?

@user-yy5rf3ly7b Год назад

Hi thanks for insights.. it would be helpful if you can share your linkedin id..

@2carlosa Год назад

Yeah! Totally agree. As a bioinformatician, I also felt some things this video reported. I think the "data scientist" role is even newer and less well-defined. So, managers and colleagues don't know what it is, which leads to great mismatches in terms of expectations... As far as industries evolve into more data-centric approaches, I guess people will be better valued...

@sumitpandit6006 Год назад

@@Arbi_kureshi ur number?? I want to talk to u

@Hastur876 Год назад

So basically, in the industry, billions of dollars or more a year is being wasted on faulty recruitment methods that waste interviewer time.

@justinat Год назад

You covered some really great points that I'm also experiencing in my current role as a "data scientist". Tbh I don't even know what I'm supposed to be doing and it makes me feel so lost especially since I'm still early in my career. I saw 2 great people leave the team to work as a data engineer and a software engineer. It's absolutely demotivating to see people leave. I'm also looking into transitioning into a more data engineer and/or product analytics role but the interview prep is super overwhelming/difficult and imposter syndrome really kicks in. 😢

@TheBjjninja Год назад

I will try to help out here: 1. Descriptive analysis 2. Statistical inference 3. Machine learning 4. Causal inference These are the four categories that fall under DS role potential scope. Any business problem one could bring up should fit into one of these four categories

@msnbmnt Год назад

Thank you for sharing this. I thought I was one of the only ones struggling super hard with the ambiguities and absurdities of the data science job search.

@DeanAbbott1 Год назад

thanks for sharing your experiences! The manager who spoke of wanted applied scientists (a category I wasn't aware of before this video) was odd to me. So he was saying that there wasn't enough data science related work for a full time hire (or else he wouldn't be wanting someone who could also serve as a software engineer). I can imagine companies having this need (smaller companies in particular where individuals have to wear multiple hats), but if I were a data scientist trying to get hired as a data scientist, I'd avoid this manager/company! I actually left a job in the 90s for this reason--I was being pulled into other jobs/tasks that weren't related to machine learning, so I left and joined a company I could do machine learning full time (I'm an old guy! I predated data science, so in that time, it was called "data mining" or "pattern recognition". and yes, I'm using machine learning and data science interchangeably even though I know they aren't fully interchangeable). The manager is key--even if you like the company, if you don't respect or are respected by your manager, it will be an awful job. Remember that when you are being interviewed, you are also interviewing them! :)

@neel6978 Год назад

last line is just gold

@redasatisfaction9638 9 дней назад

@@neel6978 Old people are gold mines, I truly can't fathom how knowledgeable are old timers !

@emoon777 Год назад

Thanks for sharing your experience, I'm embarking on the data science journey right now and it's good to hear some of the challenges so I can keep them in mind.

@TheJacklwilliams Год назад

The key here too Sundas is remembering when it’s your turn to interview them. Recognizing what questions to ask, to see if THEY FIT YOU. I’ve been in many interviews where a recruiter was selling me into a role that I didn’t fit. A few, I ended, thanked the interviewer and told them “I’m not certain why we were paired up on this. I don’t have those skill sets, nor interest to work in that area”. That’s a REALLY HARD THING to do when your junior but, being aware and avoiding that pit fall is huge.

@silenthill1035 Год назад

I am not a data scientist but have worked with some. Thank you for sharing the harsh but truthful reality of Data Science jobs. Another harsh reality is ego-boosted people Data Scientists have to work with. When a PI gets funding big enough that they can hire a Data Scientist to look at their data or design their experiment, they are on a high horse and have already made up their mind about the results they must get. For example, a PI once was so sure that he could get Nature-level paper out of the results he had that a Data Scientist had to show him that randomly generated results with some tweaks had the same properties as those he was seeing in his result to burst his bubble. Obviously they never worked again together.

@boejiden7093 Год назад

The biggest problem I’ve had so far is working with my manager. We both have very different perspectives on various problems but he simply doesn’t even want to hear my perspective even when my perspective is usually right. We are both data scientists but he graduated as a data scientist back in 2003. So he’s an old head and I recently graduated. It’s very tough to get along and having your voice heard

@SundasKhalid Год назад

I’m sorry to hear that. Having a good manager is so so so important honestly. One can be working on the hottest technology but if the manager is not good, the experience is ruined. Thanks for sharing your experience.

@boejiden7093 Год назад

@@SundasKhalid Like you mentioned in the video, companies don’t understand what a data scientist is and because of that their expectations are x and my skills are y. It does hurt my performance review which I didn’t realize until after I started working as a data scientist. I’ve heard a lot of my friends who had bad performance reviews even though they had done a lot of work. But I just think companies have no idea what to do with a data scientist when they hire one.

@jcdenton4281 Год назад

And we have to shut up cause of inexperienced argument

@boejiden7093 Год назад

@@jcdenton4281 exactly. My issue is that he asks me to do something, says no to my method, then does his way, it doesn’t work, and then we go back to using my way. Then blames me for taking too long to finish it. Every project without fail he’s done this.

@strangelyproton5188 Год назад

@@boejiden7093 same all my thoughts are completely different from him. he likes to make simple model with complicated UI. who even cares about UI if model isn't doing good. and just two days ago they have to let me go because i am not fit for organization people like him are ruining data scientist posts and outcome of it.

@kirkwagner461 Год назад

People usually leave managers, not jobs. Your experience there is not unusual. I also work in IT, and have resisted moving up to management. I'd rather be involved with the work, rather than stepping back to manage the workers. However, this has hurt my career in some work environments (Notably business, less research) where not wanting to move up into management is seen as a lack of motivation. So, for me, I've taken hits in compensation in order to support my own job satisfaction. I'm now old enough that retirement is on the horizon. I look at the size of my nest egg and contrast it with the ulcers that would have been required to make it larger, and I don't have many regrets.

@ivankatalinic2881 Год назад

So few people get this. It's not just about getting ulcers, but avoiding getting promoted to a level of incompetence. Not to offend anyone, but to be a manager is a completely different skill set that even many of those pursuing it don't fully grasp. Not to mention how even great managers aren't able to act beyond what they're allowed to do by, let's say, poor company policy. This is why there are so many inadequate managers present in so many workplaces across every possible industry imaginable. A good, great or awesome worker doesn't necessarily make a good manager. Also, being a manager isn't always more valuable than a skillful worker. (In any field) Thus, it's a shame there are examples such as yours where a person takes a hit in compensation or any other benefit for what is a silly reason.

@arcabuz Год назад

Have you ever tried to be a manager?

@priyankasagwekar3408 Год назад

Yes there’s ambiguity in role definitions. In my previous company, I worked as Data scientist. However I hardly did any data science work. It was more like a developer work where I was assigned to test and deploy the ML models in production. I could learn a lot about aws cloud architecture and services. Trouble shoot real time issues. But did little of ML. Then I changed my job and joined as Data analyst. Here I do little of analysis, SQL etc and more of ML like developing models and fine tuning them. Cleaning the data, feature engineering and feature selection. I would caution the people aspiring to enter the field because many a times companies themselves are not sure where and how they are going to use data science, what are the prerequisites for a successful data science project. They lack quality data, if they do have data- accessing and compiling the data is another issue. After aligning with multiple departments as single man army, you are expected to give some magical results. When results are satisfactory, you will be asked to deploy them. Here again the streamlined organisational requirements are missing. Somehow you drag the project. Later you are expected to monitor and troubleshoot issues in production. And then after all of this single man army efforts, management doesn’t see any value in it. Just to keep up with trend companies end up hiring a data scientist and expect that person to assume multiple roles and give them an end to end solution. They are just giving analytics a try without investing much in it.

@thecrowsnest6963 Год назад

Thank you for you honest assessment!

@calmedbythewind3453 Год назад

exactly facing the same here. How was the transition from developer work to actual ML like?

@humansoftech5905 Год назад

Thanks for sharing!

@dariashtanakova1200 Год назад

Thank you for sharing! I have a really similar story. Worked as a CV/ML for a 3 years and constantly tried to be up to date with last tech stack and ml frameworks but only few time had real chance to use them. Now I'm in process to switching to frontend.

@Pranav-lg4is Год назад

@@dariashtanakova1200 front end developer will be completely different field right ... You will need more coding html, java etc ... What are other options you can opt for?

@ToddBryantsr Год назад

Data Scientists sweat the details and this is a great asset for a product management. One casualty of being a data scientist is that you develop a expectation of higher proofs that many of your family and friends for everything. As a data scientist, I am fascinated not only by the data, but how the data was collected and obtained because understanding this often leads to more insights, but the ever present "well how do you know that is true?" question can often bump up against people who expect you to trust them at face value. I recently went back to university and the professor assigned books that had a lot of charts and tables and in typical form, I researched the data that was used and found that it wasn't up to par and while my professor agreed with me, I got the sense that she was perturbed that my discovery upset some of the foundational premises of her class. I ended up dropping the class because from that point, I checked everything and became obsessed with the data issues. If you are a person who likes being gullible -- not in a bad way, but a person who likes to believe in the good of others, think before becoming a data scientist.

@brytankak9598 8 месяцев назад

Not all DS are like this though. In my team we have all sorts, with a few barely detail focused and more excited about the tech stack and automation. They do tend to come from software development.

@jeffnogo Год назад

One of the biggest challenges I've had with being a data scientist is that DS/ML projects can be incredibly unpredictable. Managers always want detailed expectations and timelines, but when these managers have little to no DS background, these tend to become unrealistic. Me being a perpetual optimist gets me to buy into these expectations and timelines more than I should, which looks great to the managers at first, but unforeseen challenges with the data almost always hit me over the head eventually. As I build more experience I'll get better at managing this, but it's a common challenge right now.

@issa_coder Год назад

This is a very interesting perspective. Not all companies treat data scientist alike. The role of a data scientist is an amalgam of skills from various backgrounds. Unless you start in a brand new team with the same background , the feelings of incompetency and being lost when you work for a traditional company are unavoidable. The way to deal with uncertainties and fear, is to continuously learn and improve yourself in the areas you feel less confidence. Thanks for putting these thoughts out!

@LindaVivah Год назад

This is so insightful!!! Thank you for always being so authentic and an absolute queen all around. AMAZING video as always.

@SundasKhalid Год назад

Thank you, Linda ❤️

@oscarsarmiento3641 Год назад

A long time ago, I experienced similar situations in other areas of data scientists and their relationships with managers, which required multidisciplinary work. I perceive from the comments that there is a communication gap between the data scientist and the manager. Once the problem is identified, sometimes it is time to make the route and perhaps make some diagrams to educate the manager on the most convenient alternatives to solve the problem.

@preciouschukwu7149 2 месяца назад

The way you talk and laugh in between tells me you're free spirited. You got my kind of energy and i know you'd always be fun to be with. That aside, thanks for sharing this experiences as a lot are also trying to get a way around it.

@carolinaalvarez1775 Год назад

Hello! Love your channel. I'm a Sr. Data Analyst. You are spot on! when it comes to the interview process. I interviewed for a Sr. Data analyst role. I didnt apply at that point for Data Scientist bc I felt I was not qualified for it yet. One of my interviews for Sr. Data analyst was super technical and the interview was about ML, algorithms and AI. I had maybe 2 projects under my belt on that, so I didnt know all the answers and my take home assignment was ok, but I failed presentation questions. I felt discouraged. Then I had interviews at other companies for the same role and the questions were more about excel, sql, data bases, and some python. So yeah every company has different views on the roles. So the interviews can be too difficult for the "title" or too easy. You never know!

@dikshyakasaju7541 Год назад

Preparing for interviews can be arduous because like you pointed out that different organisations have different definitions of a Data Scientist role and Data Science is such an extremely broad term that is often times disputed amongst people. You only find out when you sit for the interviews that the organisations sometimes are actually looking for a Data Analyst or ML Engineer or Data Engineer when the interview doesn't circle around what you'd imagine it to be. But that's the reality and thanks for pointing it out. And most of the time I am just scraping and cleaning the data which definitely gives me mixed feelings about my job role. I could really relate to your experiences and it definitely resonated with me. Such an insightful video for the ones who want to pursue their career in Data Science because often times it can be misinterpreted.

@mysteriesphanto3528 Год назад

Basically HR don’t understand the difference between curtain jobs title so they’ll just slap anything on it

@magicmeditation3028 Год назад

What is your salary pls tell

@pragatipdalal Год назад

This was an enlightening video with great insight and I really enjoyed listening to someone articulate the challenges of a data science job when an individual transitions to a "Non Data Science" manager.

@millertime6 Год назад

I feel like tech jobs always morph: we have hiring expansions and more specialities, then we have layoffs and more generalizations. It does seem like the demand for data scientists dropped off a cliff, but I’ve been studying it a bit as a way to complement other skills. Thanks for the video ☺️

@mohit4902 Год назад

In Addition data scientists have to work pretty long hours, manage 3-4 projects and also have a poor work life health balance as compared to software engineers. Software engineers have more structured and stable lives in general. So the salary per hour is much higher for a software engineer.

@freemovieshub9607 Год назад

I'm also a data analyst, after completing college degree applyed several job, after got rejected from more then 50 companies. Got i job in one company with heavy workload plus nightshift too. Then i decided to leave it. Then decided to change field. And now i started e-commerce online business and put my all computer skills in business. Most of my work done by AI. And i really happy with my decision

@renkylo2179 Год назад

👍

@prasadjayanti Год назад

I am a data scientists & agree with everything what you have said. I found the video very insightful. I think the hard thing to sell is to convince the managers is that the success of any data science project depends on the 4 things. 1) data 2) computing 3) problem and 4) technical expertise or data science team. If any of the item is weak project will not work.

@JeGa555 Год назад

I was placed as a tester and was asked to write test cases for a data transformation project. I worked hard, researched a lot, understood business requirements thoroughly and wrote over 100 test cases. Manager still gave negative feedback to my company and I’m so furious. I’m doing masters in data science and now working as a consultant DS but they just don’t understand what DS entails and keep referring me for any role that they get asked to fill. Next time I’ll make sure I’ll pick and choose my project as a consultant DS. If it’s not related to my skills I’m not taking the project. Even though I believe in agility, adapting to changing requirements and learning but some managers are not acceptable of growth mindset and have extremely high expectations !

@mannumannu9200 Год назад

Not some managers. Most of managers

@HorologicRannygazoo Год назад

" If it’s not related to my skills I’m not taking the project." Exactly. While it can be cool to take on a project that stretches your abilities, if you know what you are good at and what sets you apart, you should find those roles where that skill is appreciated. But all of us with that attitude had to learn it the hard way like you did -- so you're not alone.

@Skaxarrat Год назад

I'm in the selection process for a Data Analyst course from a company, so thanks for shedding a light about this. Fungible content.

@shubhankarsharma389 Год назад

Hi Sundas ! Thanks for sharing the experience. I am a new Machine Learning Engineer in the industry. I think I can resonate a lot with what you said, but at the same time I believe that the industry is getting more mature in terms of the term "Data Scientist", a lot of companies are getting more process and experience driven than nomenclature driven. People spending a lot of time at a single organisation and not moving across or not communicating with others in the industry may lead to fixated mindsets and definitions about Data Scientist, Applied Scientist etc. where all these definitions can vary a lot in the industry. Also, I am fortunate enough to join the industry (especially my company) at the right time, where it starting maturing, started having understanding equal to (if not more than) engineering processes. Also, for the people who want to join the industry now can get better guidance, from more mature industry personnel and processes. (Although, I doubt if FAANG has still learned that ;))

@sumitpandit6006 Год назад

Shubhankar sir please share ur number

@brianmorgan5880 Год назад

After reading many of the comments, I've not heard anyone speak about the importance of working in a field that they love. When I grew up I first wanted to be an ornithologist, then a paleontologist, and then an astronomer. While I'm none of those now, except in an amateur role, I discovered that I really like the medical field. I did that by changing jobs frequently in my early years. The problems that I hear people complain about here are issues with corporate management. Many times there is nothing you can do about that. However, if you love what the company does in terms of a product or service, then that goes a very long way to mitigating the management issues.

@TobysDataDigest Год назад

Your videos are a HUGE inspiration!! just started out my own youtube (from my experience as a data analyst) All the best!

@TheNisiu Год назад

Thank you very much for sharing your experiences! I have a PhD in Biomedical Engineering & I can honestly say that I've experienced many of the same experiences with interviewing & jobs just not understanding of defining your roles well. I was considering transitioning to Data Science but maybe I will look more into data analytics instead. I'm burnt out at this stage & just don't have it in me to take more chances.

@platano5805 Год назад

I’ve been in the (fill in the blank) industry for ten years and never felt comfortable with the name “data scientist”. I never knew what to make of it. It just SOUNDS ambiguous lol To those on the struggle bus, I get it. My recommendation: I’ve always marketed myself as an analyst, highlighted the systems and languages I’m proficient in, and provided demo’s of past projects. Then, ask questions of your employer. Interviews are as much for them as they are for you.

@mves685 Год назад

You were definitely not wrong to be offended by your manager's comparison. I had a similar experience where my manager decided that only ppl who can make good data scientists are ppl with PhDs in physics, and he decided to only interview them for the role from that point on. I only have a MS, and it's in math, so whenever he brought it up how we need to make sure we get in "quality" people by having this filter, i got pretty upset

@lovathon6365 Год назад

if i had a PHD in phyics... i wouldn't be working at a company like that lol id rather be a prof or working at a company that directly uses physics for the job (like nasa/etc) but never for data science

@asdfafafdasfasdfs Год назад

Out of curiosity, what was the background / qualifications of your manager?

@mves685 Год назад

@@asdfafafdasfasdfs One of them had a PhD in Physics and the other MS in business. So i think the physics one decided he's the only qualified one, and the other guy was just impressed by the degree and went along with it

@felipegmuniz Год назад

Thanks for the video. I was actually waiting for some DS to expose a bit of the harsh part of the career.

@mamzy1465 Год назад

Thank you so much for this. I thoroughly enjoyed your honest perspective and learned a lot. Keep at it!

@SundasKhalid Год назад

Glad you enjoyed it!

@pedromarques9267 Год назад

Sundas, you are right that we should judge if the role is good for us from the interview questions. We shouldn't forget that the people they hire before us went through the same questions. Do you want to work with a team of Data Scientist that only know what they are asking in the job interview?

@chriss5745 Год назад

I totally agree with you. The hardest part for me is to deal with those "data scientists" who barely scratch the surface of this world. I think that this stems from the problem that data science actually begins where one usefully combines the domain expertise, analytical data understanding, mathematical approaches, algorithms and all those software tools. There is soo much to learn, it will take you about 5 years fulltime on top of a basic MINT subject until one really knows what we are doing. Many beginners don't see this and can't understand it how hard this actually is. And the payment isn't worth it in most cases, because your managers won't understand this either.

@kelvinortiz9188 Год назад

During my last 3 years working in data science, I’ve always felt isolated. I haven’t had the opportunity to work with data teams, so it’s always been me as the only expert..

@mysteriesphanto3528 Год назад

In a way I don’t mind being isolated from people but at the same time I wouldn’t want all the work load put on me

@neel6978 Год назад

@@mysteriesphanto3528 what would you choose instead the DS with the knowledge you have now?

@mysteriesphanto3528 Год назад

@@neel6978 probably software engineering

@svdfxd Год назад

You were spot on...the other problem that I have seen is that some Data Scientists instead of doing Data Science work are more interested in Data Engineering work...because they think that they might loose on their technical skills / they love that work more than working on Data Science projects. I agree with your first point that if you have good communication skills you could be drafted in a Product Manager role...this happens even in the tech stream. If someone is good in talking to people - esp. in service companies - that person is asked to manage the team and he is told that you will be doing 25% coding and 75% team management...but trust me it become >100% team management activities.

@wusswuzz5818 Год назад

A sizable part of product / project management is data analysis / analytics, so its not unsurprising to see the easy transition.

@LearningandTechnology Год назад

A problem may be that a lot of companies are not far enough along on the data maturity model to actually use a Data Scientist effectively - so then they are surprised when they aren’t getting the results they wanted.

@datasciyinfo5133 Год назад

Totally agreed. Except for Big Tech, they don’t have the kind of user data or logging data that is ready made for current DS/ML tools. It takes more thinking to figure out a good way to use the data they have or figure out how to start collecting data that would be very useful. Maybe the Data Science role will also evolve. Most regular businesses will use the AutoML via chatGPT, and only those businesses that require maximum data knowledge will have Data Analyst/Scientist/Engineer/Strategy Consultant/Business Forecaster/Decision Maker etc. And it will be one giant field with many levels and sub fields.

@motazyasser8994 Год назад

This is very helpful..and its relieving too feeling those are usual problems we all face

@structormodeling7728 Год назад

Thanks Sundas! Helpful as always

@vectoralphaAI Год назад

I am a recent graduate in Computer Science and want to instead go into Data Science industry instead of the traditional Software Developer/ Software Engineer career. So as someone like me who eventually one day wants to work in data science industry, is there an entry level job role that one can apply as a starting point and just get promoted/ level up to a data science in time rather than just trying to apply for a data science position from the get go? I dont mind starting at the bottom and working my way up the ladder. Anyone have any suggestions?

@brianobush Год назад

I have been working in this area for over 25 years (way back before the data science tech tree). Companies are still trying to grapple with this domain and I tend to stay away from companies that don't really know how to use data science. My recommendation would be to stick with companies where the core technology is based on data science/AI. E.g., speech recognition, however, this gets to be more applied science work and usually requires a bit of training in the specific domain.

@willemmerson224 Год назад

I think this is the paradox: companies that uses and understand the topic appreciate the work, but yet have higher expectations on the offered skills. Because they have also an established team in place. In contrary, companies that are merely in the beginning utilizing it having a hard time to define what skills they need, how they trying to achieve it, and fuzzy about the work you must then do. Yes, avoid them if your already at senior-level.

@thebrandonian Год назад

Nice! I see you use the Momentum extension in chrome. I've used it for years. Such a good extension. Soo thank you for this video. You gave some good potential warnings. I am completing the Google Data Analytics cert and think it might help me in my current job. I planned on taking a Data Science cert after but I'm not sure. It depends on how things go but perhaps I still will. I'm confident I'm capable, even after listening to your points. But I think I have a better expectation now. Thank you :)

@shubhamjoshi8117 Год назад

I completely agree to what you say , the issue is the existing product manager are unable to think datascience solutions for the product. I have seen a lot of products where they should consider AI features primary they end up treating those as secondary. This makes their product outdated. I understand what you said about applied scientist, but its a hard fact.

@poppins586 Год назад

I have also worked in Data Science for 9 years now. I worked as a data scientist for my whole career until now. I was hired in direct as a Senior Software Engineer in Cyber Security. It's actually a really smooth transition.

@Ricocase Год назад

What does data science have to do with cybersecurity?

@poppins586 Год назад

@@Ricocase a lot more than what some might think. Think of this, code is data. Cyber security professionals want to eliminate exploitable code. Therefore, AI should help us find the vulnerabilities.

@magicmeditation3028 Год назад

Pls tell what software engineer do

@aragorn1780 Год назад

I spent the last 2 years learning data science while applying everywhere to get my foot in the door what surprised me was just how many roles there are out there that require data science/analytics skills but aren't themselves data analyst roles, they could be logistics/managerial roles at a warehouse, I've seen loss prevention roles need data skills, sometimes they turn out to be nothing more than data entry roles, quality control roles, etc etc and then of course the actual data roles themselves swing considerably, sometimes it's a business/financial analyst role and you're just pulling down charts and graphs to put on reports for the big wigs, and sometimes it's actually a full stack dev role that happens to include SQL and R in its language requirements, oh yeah and DB administrator roles which turn out to be IT helpdesk roles lol

@kingsleyiwobe2415 Год назад

Thanks for the guide. Its great to know the reality of any thing of interest.

@waynelast1685 Год назад

My impressions of the industry is that there is so much skills/experience overlap , and companies look for multi-faceted workers, that there is some confusion in the hiring and project phases. One confusing aspect of this industry (Data Science) is not everyone has to be educated in Computer Science ( with degrees). So that leaves a lot of open-ended questions sometimes I think. I do not have a computer science degree (but I do have BS and MS STEM degrees). So I was surprised when I found out I could make entry into this field ( I am highly analytical and love math). But like you said companies want "fungible" ie, multi-facted workers SOMETIMES, not always. I can understand that.

@ronaldmassey5029 Год назад

This is how I feel, first you work 2/3 or more of your life, so I believe that you should be happy working at whatever job you want. I,m 75 and last year just started programming with Python, got a long way to go though, but Data Science does sound interesting. I pray that you will find the meaning of your work and not let someone decide it for you. Lots of luck.

@preciouseze1289 Год назад

75?😳😳..you need to rest...why bother yourself learning

@clarazegarelli5861 Год назад

good advice...

@dwaynevictor228 Год назад

😂😂😅

@WishesCameThrough Год назад

@@preciouseze1289 stimulating the brain especially at old age helps prevent brain pathology such as dementia

@dianyadira Год назад

My husband was referred to a data science role by a colleague and he was unsure about the role. It was hard for him to prepare because it seemed that people and organizations would use data analyst, data science, data engineer and applied scientist interchangeably. I am learning about it now since I have been wanting to get out of cyber security. Hope for the best.

@flow1465 Год назад

Is cyber security not worth it for long term? I was thinking of pursuing this field.

@zubinpratap Год назад

@sundas I really hope people pay attention to how managers and industry experts THEMSELVES have hugely different views on what roles/titles/terms/scopes mean. I've seen this in my previous careers but its very true of DS/DA, SWE and PM roles. This is why being very thorough in research, self awareness and market intelligence is critical. I've interviewed for roles where the FANG folks use terminology that has a VERY different meaning in other industries and NEITHER side knew it 😅

@GonzaloArangoF Год назад

Quite interesting!! Please, can you produce a short list of the most critical questions that are important to hire a Data Scientist for an organization? And the complement: What are the most inadequate questions done of Data Scientists, and what inappropriate tasks are requested of a Data Scientist? Thanks for your insights!!

@TheBjjninja Год назад

When you get to a Senior level, things will become more clear. The low level work gets assigned to level 1,2,3. So when you really add value to the business and can impressively demonstrate your abilities regularly that's all that matters. These complaints about the DS role are all low level issues IMO.

@ZFlyingVLover Год назад

The 'harsh' reality of being a data analyst is that its really just 1 skill in a toolbox a good programmer has. That along with ML, microservices, event based programming.

@TheCrystalCort Год назад

You make great videos and talk about all the things we are thinking but don't talk about! Thank you❤️❤️❤️

@mdsaidulislamsayed1136 Год назад

Yaayyyy!! I am your biggest fan Sundas! love your informative videos as always!

@talkNoJutsu1.0 Год назад

I am learning Data Science from last 1 year, I had taken an online course and gave it full time means not done any job in that meanwhile. Now no one wants to hire a DS fresher with a career gap. All the internship and fresher job descriptions are scary to even look at. Companies are using buzz words like Data Analytics for Data entry jobs. Each and every job description is bombarded with various technologies which have career in themselves. Felling exhausted and frustrated from this whole Data Science thing. I know Data Science itself is an elegant career but due to the industry environment, I am learning Backend development now, Let's see what will come out of it.

@mateovansweevelt5257 Год назад

I think one of the main problems is that there is still so much confusion about what a data scientist really is. Granted this has gotten a lot better over the year, but we're still working on it. Most recruiters have a difficult time figuring out what the role of their version of a data scientist entales, let alone communicating those needs to potential applicants. After all, the people that create these job listings aren't technical profiles and don't really know what the company needs in terms of analysts, scientsts...

@Neowave40 Год назад

I have been a junior data science for a week now, this week was filled with a lot of learning and frustrations. My first assignment was to analyze and evaluate the results of a computer vision model and its classification model. PS: This is my first time manipulating images.

@Chanelle-pr1op Год назад

Hello, Thank you for sharing your experiences. I don't think you are alone in feeling frustrated about others not understanding your job. Back when I first started out as an administrative professional that was exactly what I dealt with. Not only inside the company I worked for, but also when I ventured out to apply for other positions. This was decades ago. Now, I'm starting to understand why that was the issue, that a lot of people in various positions have the same issues, and that this frustration can be a great conversation starter. ☺ From what I've learned about Data Scientists vs. Data Engineers vs. Data Analysts, Data Scientists are at the top of the hierarchy, so a transition is necessary when people want to grow in their career. Also, a lot of jobs including HR, Marketing, Sales, etc. want people to understand enough programming in SQL, Excel, and metrics to perform at least a Data Analyst function. Technology is moving fast, and being in the industry for nearly ten years has probably put you in the middle of a lot of change that no one anticipated, so new grads are coming out with hybrid knowledge that the rest of us have to adjust to. ☺ There are EMDR patting techniques that help relieve anxiety. Here's a link to a video. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-iGGJrqscvtU.html I haven't watched the whole thing, but the first thirty seconds makes it seem like it's what I mean. Hopefully it helps. Thanks again.

@supervince110 Год назад

Me: data scientist who is experienced with ml and dl. Boss: let's solve this super complex modelling problem without using ml or dl.

@gupta-vibhu Год назад

Agreed that managers wont appreciate your usability. I urge you to guide us how can a data scientist work as a freelancer or a individual entrepreneur. In essence, elevate him/her from an employee / subordinate position.

@gospelmoto2833 Год назад

Thanks for this info. Im currently having lessons on DA course. Nice to know your revelation. Got a new subscriber here.

@roopaization Год назад

I resonate with what you say. There's no clarity in job roles description and preparation for the interview is really hard.

@Hari983 Год назад

I left the whole career line before I even really began! I studied Business Analytics for my masters with data science intentions in mind. After over five hundred application rejections (yes a real number - I'm an international graduate which makes competition way more intense) for jobs that are actually (looking at the requirements) obviously intermediate but for some reason termed as entry level, I decided to forget about this whole line altogether and focus on actual software development. Now working as a Unity game developer, and with my strong frontend development skills planning on taking on a frontend dev job next. At this stage I'm not interested in the least in anything that has to do the data science and it will probably stay this way.

@milanacharya4865 Год назад

Hi Haritha, I have am in a similar situation like you were. Do you mind communicating with me regarding your journey? I would truly appreciate it.

@watchwithnicky7140 Год назад

@@milanacharya4865 i learned data science but didn't get a job because just after i finished my course the lockdown happened so after the lockdown i joined as a javascript devloper and learned nodejs amd reacts ...i am again thinking to switch in data science....so should i stay in MERN stack or should i move to data science...please reply as soon as you see it

@ericj5572 Год назад

This is soooo spot on and this made me feel so much better. I went on so many long interview process and then they would just ask me “SQL” questions..I was baffled..

@josephshaff5194 Год назад

Well there are times when some statistical studies are used in the early phases of Product Design to discover what consumers or customers mostly desire in the product concerning it's function. Then it goes to the Engineering Teams M&E to Design it in. I see quite a few of them now.

@CharuSantoshSaraswat Год назад

Yes, you work with a very trendy name, and few problems you mentioned, comes with trends! You are too Good :)

@rahulrahul026026 Год назад

hello mam, love from India I started my data science journey from last 3 months. I successfully completed python,pandas,numpy,and sql right now i am lerning statistics. i always come to your channel whenever i need some clarification on data science and i also followed you on linkedin . thank you so much for making such amazing videos.

@abhishekjadhav4105 Год назад

Where r u from

@rahulrahul026026 Год назад

@@abhishekjadhav4105 uttar pradesh

@mirthplay4660 Год назад

How i start my journey as a data scientist from another field? what's the basic knowledge i have to start with

@rahulrahul026026 Год назад

@@mirthplay4660 RU-vid, udemy can help you.

@ramshaafifa7232 Год назад

How r uh learning data science

@ttovar17 Год назад

As an entry level role for those entering in the field. Which path of these 3 roles would you say is best to begin and progress through... Data Engineer/Data Scientist/ Data Analyst? I've studied each and doing projects but equally like each as they somewhat overlap. What is more realistic junior opportunity to get hired in first?

@movievibes521 Год назад

my suggestion would be da-de-ds bcz it would be incremental learning and you will be have strong base as data scientist

@ovantry1385 Год назад

@@movievibes521 but i hear somewhere to do first: DE then DA and then DS. Because DE is capable of doing all things of DA and DS. But just he is very busy. So DA AND DS take care of the rest. Plz explain your point of view. Thanks!

@JasimaSyed Год назад

Thank you Sundas! Appreciate your insights. And "fungible" tickles me too 😂

@deedeeOWL Год назад

Wow thank you for your genuine insights 🙏🏼

@Videofiziert Год назад

I honestly think "data scientist" is a job title that is too young yet, HR people usually will take a couple of years (or decades) to wrap their heads around what the job entails and what kind of people they're dealing with. I mean it's been 40 years and they are only now beginning to grasp the role of software developer ^^

@acdude5266 Год назад

I was trained as a statistical analyst in what might be called classical regression, DOE, and inference. At work, I analyzed data and leaned as much as I could about what is now referred to a data engineering. But, it was extra. Now, a data scientist is more like computer science or data management than statistics. I think that executives drove the push from data visualization because there was always antagonism with control versus the need for specialists in an esoteric field. There is still a need for understanding of the classical methods, yet most companies outside of clinical trials have jumped on the AI/ML bandwagon. Add the increasing chasm between management and staff, the vagueness of the term data scientist, and this gartner stuff and it seems like instead of simplifying and harmonizing the field per Jeff Wu, it seems oppositely like total anarchy, fad chasing, and terminology babble to me.

@mariaclarissafionalita4015 Год назад

I am also pivoting from business school to data science and I have also been told I am better off pursuing product manager roles even though I have never expressed any interest at PM roles. I guess that's just how people who have business undergrad degree are perceived.

@tjs1352 Год назад

The role of data scientists in my company is quite ambiguous. My job as a data scientist is more like a tester. Some of my colleagues whose job title is also data scientist are more like developers. I spent most of my time studying business logic, looking for something inappropriate in the current system, and trying to find a better way to build analytic models. Some of my colleagues spend most of their time realizing the model, tuning parameters, and refining models. If we are going to turn the analysis into a product then I do most of the design as well as quality control work like a product manager and my colleagues do most of the implementation work. I guess it's more appropriate to give us different titles, like data analyst? scientist? engineer? I need to turn to a dictionary to tell the difference lol.

@MrScotchpie Год назад

I'm in my 50s and the only thing I can add is after 20 or 30 years the job becomes totally boring but you are stuck in the job because of the pension. I would advise younger data professionals to increase your skill set and transition out of the field because after several decades, its a completely boring job yet you still have to keep on top of latest developments, read papers, attend conferences etc when in truth you are really not interested in the job and you just want to go home, tend to your garden or finish that hobby project etc.. Roll on retirement.

@FearlessBolt Год назад

Which career would you suggest us to transition in?

@dontbotherme9009 Год назад

You're lying. If so where to "transition out of the field"?

@MonsieurSchue Год назад

To be fair you said it yourself already that data science actually covers a family of domains or jobs. But I think indeed DS job is still too new and really rides on a lot of hypes and so a lot of the companies just didn't want to be left behind yet at the same time didn't really know what they're doing themselves. Also in reality there is yet to see that many companies (or even industries) truly benefit from having a DS or even just ML team from the business standpoint or profitability point.

@arielguzman2875 3 месяца назад

Interesting. Never heard of an applied scientist before. Great content. Thanks

@javnon1 Год назад

As a project/maintenance engineer I can say that most of the point that you make could be applied for job types. Titles are just titles is always important to understand to “what needs to done for job/company “ . It al depends in the company that your going to work in which you will only truly understand after a few months…

@abdullahrizwan668 Год назад

Heya! I dream to be a data scientist but i'm bit confused what degree program I should take.I mean is it better to go for 4 years software engineer degree then do masters in data science or do 4 year degree in data science and apply for data science job?Please help

@islamicsolutions7800 Год назад

Have you decided?

@mwredfern Год назад

My company hires a lot of data scientists, and then tries to turn them into data analysts. Why? because the hiring managers are data analysts. and are too lazy to learn even the basic fundamentals of data science and machine learning. Hence, why we have almost 100% turnover in data science. usually, every 6 months.

@nurefsandavulcu6460 Год назад

This is exactly it.

@nurefsandavulcu6460 Год назад

This is exactly it. "We don't really do that here" was the response I got at my company when I expressed interest

@Kay2049 Год назад

Thank u for your video. I thought that I was the only one feeling this way about the industry.

@westoncorpengineeringindus4506 Год назад

Très instructif cette perspective. J'envisage ce métier mais en tant que Maintenance and reliability Engineer

@AnotherAnalyst Год назад

In general in IT if you have good communication skill than everything become secondary, you can take leadership track and manage bunch of people who are great coders but cant talk well and prefer to deliver quietly. We call them coding monkeys 😬, just tell them what to do and they will code happily and come back for more when done. In long run, its the leadership that brings money, fame and success and not the stand alone work.

@b1ackwollf Год назад

its people like them who dont have patience and analytical skill to do coding and only knows to talk. sadly they are paid more

@HarshvardhanKanthode Год назад

And we call managers who know nothing about the product they're managing, trash managers because they will never climb the ladder using jargon and empty platitudes

@jnjnijl. Год назад

time to change my ambition

@Anselm243 9 месяцев назад

The reason why company’s don’t understand what a Data scientist is because it was a up job title by Facebooks lead software manger back in 2004. They wanted to hire a really smart mathematician to understand there data but he wouldn’t take the job because he didn’t like his Job title. So they told him he could pick his own job title.

@chrismachabee3128 Год назад

Well, I have two things. A product Manager has a lot of responsibility, and you're dealing with a lot of people, and a former Ddata Analyst you are not overwhelm dealing with number behind the product. Regarding the monotony as cleaning data, I think a lot of people don’t quite under understand the importance. I am studying ML and AI, bout who really on reliable data, that come from clean data. I guess one you know how to do it is not an issue, but I think perhaps people don’t really think about how important correct and clean data is o the process. Fungible. Defined as, able to replace or be replaced by another identical item; mutually interchangeable. You brought an interesting point about interviewing. Who is the interviewing and what is the background? You said one interviewer asked you about SQL, where you can program SQL to give answers, when you have different sets of data, perhaps before cleansing, in a general sense. I'm still a baby. I am on several paths right now, and I have avoided Data science thinking I do not have the math background, but it appears it isn't only math that is needed, and not enough people to do it. Product management, as you said is a communicator’s job and a newbie lots a lot and every day is different. So, I guess the promotion ceiling in the Data X grouping is not so alluring if some has aspirations of leadership. I don't know. We'll see.

@andrewwhooo Год назад

I believe there is a massive discrepancy in "the perception of a true Data Scientist role" between the industry and job candidates. When you use data to solve a business problem, it is data science. On a high level, DS can be categorized as analytics, ML + inference focus, and data engineering (this is What LinkedIn and Airbnb categorized). When you say "A true Data Scientist" in your above video, you are referencing "ML or casual inference focused" DS. However, the DS field has become more specific compared to maybe 10 years ago when only the ML-focused roles were called DS. When you say you got asked only SQL (and I assume product case questions, like a consulting interview), you refer to a "Data analyst" role. However, these are also called Data scientists with an analytics focus. The boundary between data analyst and analytics DS becomes blurred, and I will use seniority and scope of work to differentiate them. If you are solely searching for ML focused DS, you can apply for "Machine Learning Engineer" or DS with an emphasis on modeling in their job description. I do have to mention that the (Product) Analytics-focused DS has a very large demand. Meta, LinkedIn, Airbnb, DoorDash, Uber, Spotify.. all these big names are hiring for these positions.

@neel6978 Год назад

hello. I read your comments. what would you suggest for someone 29 years old lawyer (masters) who just wants to get into the field? would u suggest getting into data science and working for law firms? analyzing data to help the firm grow?

@neel6978 Год назад

@TDDMS Год назад

Whether you are a data scientist, mech engineer, etc., you should want to do that role because you love the subject. You don't study those fields because you want to get a good job. You don't study those fields because you want to move up the ladder as you said. If you want to move up the corporate ladder, it would be wise to learn necessary business courses like marketing, finance, leadership skills, et al. Learning data science to move up the ladder is a poor career strategy. The purpose for working at a company immediately after school in any of these specialized is to pay off your student loans and put money in the bank. While you are doing that you should be learning how to develop your own business on the side in the field of study you love. That way you can just leave your corporate job and don't have to worry. There are a few red flags in your video about yourself. The fact that you are referring to your coworkers as family doesn't bode well. They are not your family, they are your coworkers. They have their own aspirations, which more than likely differ from your own. Your family are the kids you make and the man you marry. And considering you're 31 years old, the fact that you are calling your job 'family' tells me you have some misplaced maternal love.

@Krorin Год назад

With all due respect, I think you misunderstood. She's not saying that her co-workers are her family, she is saying "job family" as in "group of jobs". On another note, your family is not necessarily "the man you marry and the kids you have", that is for each person to decide for themselves ;)

@portakalagaci Год назад

For data driven decisions choosing a focused data scientist looks like a good match for Product Owner/management. It is common and it works well

@libbyheeren Год назад

You're not alone 😂unfortunately! All of these experiences resonated with me!

@danilemosjs Год назад

All data scientists with RU-vid channels explaining all carrer's pros and cons are doing god's work for us that are trying to break into the field. Thank you for your time and shared experiences.

@SerobZeromintis Год назад

fungible

@SundasKhalid Год назад

I can’t with that word anymore 😂 gives me trauma 😭😂

@StephenGillie Год назад

Some of these experiences are common to Tech work these days - job requirements can be a joke sometimes, dressing up the job like a desperate person on a dating app. One person's infrastructure engineer is another person's security engineer and a 3rd person's cloud engineer. At my last job, my job title in Active Directory was "Contractor".

@farrongoth6712 Год назад

This sounds exactly the same experience of a lot of people in similar industries mainly tech industries, I have similar experiences as a software engineer. Specifically to the hiring anecdote, most likely it is because business pressures. They don't feel like they have enough people to do the work because it not being done as quick as they would like, and they think throwing more people at it will work, the different job title will because it will make them feel they have more diversity in skills if the job title is different.