What Professional Data Scientists ACTUALLY Do
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- Опубликовано: 29 июн 2024
- Sign up or learn more about SharpestMinds here: www.sharpestminds.com?r=ken-jee
We often see the best parts of being a data scientist in day of the life videos. In this one I tell you what the whole experience is like. I want to talk to you about what data scientists ACTUALLY do, not about just the fun parts of the job.
1) There is no one size fits all data science job. You can find what you want out of the variety of opportunities in the domain
2) Project management for data science is a real thing, you're going to have to get familiar with the tools of the trade to have a good experience
3) Different types of projects have different expectations. You have dramatically different responsibilities if you're working on long term or ad hoc data science projects
4) Git and versioning is a must learn for working with data science teams
5) Learning to work with production and development servers is a big difference from personal projects
6) Tools and languages you use vary dramatically by team
7) Work is not always as exciting as you expect, your main responsibility is to drive value to the business
8) Ambiguity is a major part of the role
9) Not everyone loves data scientists in your organization
10) You sit down a lot
11) You get to work on mostly interesting projects
12) You are surrounded by learning and opportunities to expand your knowledge
13) Work / Life balance is usually pretty good
I got the idea for this video from my friend @fknight . His video on what professional software developers actually do ( • What Professional Soft... ) was a great take, and I thought that this could potentially be even more relevant for the data science domain.
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0:00 Intro
0:50 Variation in Data Science Opportunities
2:23 Project Management for Data Science?
3:42 Types of Data Science Projects
5:38 Do you Collaborate?
6:33 How SharpestMinds Can Help
7:25 Quality Control
8:00 Can you choose what tools you use?
8:41 Types of Data Tasks
9:40 Be Wary of These
11:27 The Good Parts
13:05 Sharing Your Awesome Projects!
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Thanks for watching everyone! I hope you have a better understanding of what it is like to be a professional data scientist! Sign up or learn more about SharpestMinds here: www.sharpestminds.com?r=ken-jee . Again, SharpestMinds is a data science mentorship marketplace that only gets paid when you land a job!
Im 35 years old, and I just started my Data Science journey by starting college this semester. Been an aircraft mechanic for my entire adult life and been looking for a change for years now and you inspired me to finally pursue Data science. Thank You Ken, I'll be tuning into your channel just to keep my 'ear to the ground' in this exciting field. Also, not sure if you spoke on this before, but what laptop do you recommend for data science? Thanks Buddy and keep up the good work!
This is awesome! Excited to hear where your journey takes you! I personally use a Z book studio from HP, but to be honest, I think almost any computer will work these days. A huge portion of data science can be done on the cloud through google colab, kaggle, or deepnote. This lets you use their compute power rather than the one on your local machine. Their offerings again are free and are plenty for those getting started.
Why not data analysis?
I’m in the same boat. Good luck George!
That's awesome!!!
@@KenJee_ds Awesome! Thanks for your response and the info 🙂
One of the most important things that I wish more people would do is documentation. Of datasets, sources, code, rationale etc. I often have to spend a long time on the dataset exploration phase of the project and trying to figure out things. Everything would be much smoother if people created detailed documents on the different Datasets, how things are collected, what features are used, distributions etc
Can't believe I left that one out! Great call!
@@KenJee_ds this is something I've been frustrated with recently. I often have companies reach out and dump projects onto me. But because of the lack of documentation I end up wasting a lot of time with the details of the dataset. It would be avoided if documentation was stresses more
This actually answered a couple of questions I had about working professionally. I know that SW Engineers typically work in an agile framework but wasn't sure if Data Science followed that same trend. Thanks Ken!
Now to watch this 400,000 more times so we can beat Forrest.
Thanks for watching! Yes only a couple hundred thousand more views 😂
Thanks Ken! Excited to enter this Domain!
That’s a great concise video summing up the role of a professional data scientist, this video came at the right moment as I transition from academia to industry and totally relate with many of the points mentioned in the video. As mentioned in the later part of the video, I also find the undesirable aspect of data science to be a double-edged sword as on one end the ambiguity may make things unclear but at the same time also leaves room for experimentation and innovation. Papaya Tracker sounds like an interesting personal project!
hahaha thanks for watching Data Prof! congrats again on the new role!
I think ambiguity is a good thing, a plus, as You are free to select or "find" projects You like
Yes. Outstanding video on this topic.
Thanks for the video Ken ! I can relate to everything you said and also about Asana and the tickets lol .. Hopefully will get used to them.
Glad to see you again !
Yes!
If you want a role where you want to work only with AI and heavy duty programming go for a machine learning engineer job, if you want to do statistics and sometimes classic ML and analyze data go for a data scientist job.
Working as a ML engineer you spend way more time reviewing and maintaining code (so it's more SE from one side), you use python for model development and c++/java for production (the role is building AI products, so you are all day reviewing, extracting and preprocessing data to then training ML models, evaluate them and match required KPIs)
In the other hand, data scientists positions offer what is described in the video: statistics and data preparation (engineering) and classic ML, there is more flexibility regarding tools and programming languages, and the final purpose is bringing value in a business perspective with the projects you have
For example, In ML engineering you get assigned some set of models that you have to maintain and improve, in data scientist positions you get several projects that constantly change. Both roles have their advantages and interesting scopes
I have been in both, my background is in statistics and I have been working as ML engineer in computer vision in the automotive industry for the last 3 years. Personally, I can say ML engineering is more fun, even more in start ups where you feel you bring a lot of value with your ideas about crazy AI methods
agreed!
Thanks for the great video Ken!
Thanks for watching!
Thank you for posting this video. This past year I migrated to a new work role and am listed by my employer as a data scientist. This video confirmed my understanding and also cleared up confusion as many people, my employer, and consumers of our products have different views of a data science work role.
Really glad to hear it was helpful! Thanks for watching!
This video is amazing it literally sums up most of the work data scientist do. I love the first few sec because that's literally me in the morning when I open my mails haha. I think the project management is very up to the points the data scientist role and project manager role has common things is all softs skills and managing work and which is very important in data science job role.
Any video coming up on what data engineer do?
Thanks for watching Shruti!
Thanks for the detailed explanation.
Thanks for watching!
I am really liking the Sharpest Mind's concept and something definetly worth looking into
It is super cool!
Awesome video, it gives us so much hidden information that is actually practical.
Thank you for watching! Glad you found the info practical!
Man it's been a while since I've come here to comment. Always great content master master ken! Your videos always help motivate to improve my skills each and everyday.
Really happy to see you back in the comment section Justin!!
#TeamDataScience
I can TOTALLY relate with everything you said!! Great video, people who is considering entering Data world should see this video and know thats the way it is in real life
Thanks Aaron!!
Finally ...Great insights 🤩
#TeamDataScience
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I'm working as an Associate Data Scientists at a startup and I honestly haven't needed to code for like 5 months. They've got me focused on an e-learning initiative.
That can happen! Are you wanting to code more?
@@KenJee_ds I'm not really sure Mr.Ken I just chose this field because everyone else was, I don't particularly enjoy coding, but I do like the concepts and statistics included in data science. I was actually trying to be a sketch artist for a while and stuff between jobs but life happened and I had to find work quick. And I'm not sure if I know what I want to do.
@@greatwhitesufi yaa, I kind of know that feeling, I'm always stuck between art and science too, cause I feel like I have a mind for both.
I have decided to pursue data science as career and art as a personal work that is solely mine and no one else's business. I hope that helps you.
@@virinchimarrapu5371 thanks man, and yeah I'm pretty unsure of what to do with myself at this point. Essentially I'm living week-to-week and whatever happens happens with work. I'll keep trying to be happy with it for as long as I can.
Wish you the very best man, I can definitely relate and I'm sure you will find the path as you keep going and so will I 🙂
Great video…it gave a good overview of the data scientist job. Thanks
Thanks for watching!
Subscribed within the first 2mins. Thanks for this
Hopefully the remaining 12 mins made it worth it haha! Thanks for watching :)
I’m 26 and I have one year left in my Data Science curriculum, plus my master’s program. Currently learning MySQL and I’m trying to learn Python and R on the side. It’s really tough since I’m in a data structures course using Java, and that takes up a good bit of my time. Hopefully it all works out for the best.
Also trying to get a good grasp on machine learning and deep learning principles as I go, and making sure I’m sharp with my statistics and linear algebra skills.
Awesome!
Are you almost done with a masters in data science and they haven’t made you learn Python or r?
A great explanation Ken Jee ♥️
Thanks for watching Roshini!!
Cheers man!
Thanks James!
Ah but you didn’t reveal the ultimate secret: ignore XFN unless they ask you at least 2 times 🙃 and then say that maybe you can do it next week to manage expectations 👍
lol
Miss the times when data science was simply called statistics. Now every company wants a “Data Scientist” that can do:
1. Business management.
2. Presentations.
3. Data fetching and collection.
4. Research.
5. Model building and deployment.
6. Model performance evaluation.
7. Cloud environments.
8. Database administration.
9. Pipeline building and management.
10. Client management.
With statistician the responsibilities where quite clear because now every person that works on anything related to data is now a Data Scientist.
Because Data Science aint just abt stats hence the name??? There's the domain knowledge and production aspect, not simply programming everything in R like whats statisticians did back then, now its all abt production and deployment
@@johnwig285 That’s exactly the problem. Deployment and production is more related to SE than DS. Domain knowledge was always part of a statistician job (how could he/she then build their hypothesis?)
Scope is definitely a problem haha
@@KenJee_ds True! Ken any upcoming reviews of a DS Z by HP workstation?
As long as the company continues giving me the tools to succeed or allows me to build a team to fill my gaps, I'm all in with my multi-hatted role!
Disclaimer: reality and experiences may differ
Thank you so much for this vídeo.
Thanks for watching Victor!
0:45 Challenge accepted! #TeamSoftwareDevelopment 😄
🚀! Thanks again for the inspiration for the vid!
not all decisions are mad with logic. this hits really hard the long you work in any field :)
So true!
I liked that, you ended a video on positive note.
💪
Great job man,
Data scientist from France.
Thank you! I appreciate you checking out the video!
Currently completing a data science apprentership within the forestry sector. At the moment, I am still finding how to tie what I am learning into work but I am sure it will kick in once I get to machine learning and AI (in 2nd year out of 4.. so still doing somewhat foundational study)
Came from having done a degree in forestry, and I wanted to go into research.. came across this during lockdown and thought it would be along the same lines and I would be working in a company I was interested in. :)
I am settled into a team and with that, I have got ideas.. I just need to make time to explore it and figure out how to start :)
Sounds really cool!!
Very informative
Thanks for watching!
I want to be a Data Scientist in the future. So this is gonna be good. Haven't watched the video yet but I'm liking this because I'm team Data Science all way.
Hope it ended up helping!
@@KenJee_ds Yes it did! A lot. Thank you for making such a good video. I really enjoyed it and it was really interesting.
For anyone curious, the project management framework he’s talking about in the video is “agile”
Yes, thanks for calling this out! I should provide more links in to resources in the description.
Great and awsome ❤❤❤
One of the best reveals I’ve seen about data science. My question now is if it’s better to be a product manager or project manager? Autonomy and authority are some of the most important job factors for me. Are the product and project managers literally managers to data scientists and software engineers?
Thanks for watching Max! I was a product owner for about 6 months and personally didn't like it. I felt like I kept having to track down people and that I was a glorified babysitter. To me it was the opposite of autonomy (had to interface with the business way more). This could be different in other companies, but that was my experience
@@KenJee_ds thanks for sharing that and will keep that in mind.
Thank you for this! I am trying to change careers to Data Scirnce and was wondering if companies offer on the job training. I am in my first semester of a masters program, undergrad degree in mathematics, but have 15 years work history in heavy construction. I would like to gain as much work experience as I can while I learn. In construction we have apprenticeship programs.
11:02 "sometimes kevin doesnt want to use the stupid dashboard that you built and spent 7 weeks on because he doesn't like the color scheme and he wants to use pie charts all over the place"..... Had me DYING 💀 I had to pause it. I played this clip for my husband *not a data scientist* and he laughed because THAT is me while I'm working from home.
hahaha glad you enjoyed it Kristin! Thanks for watching!
Ahhhh i'm in high school and really interested in data science and plan on majoring in it.. i just am a bit chary on the math involved because I'm unsure on how much and why math is involved in the first place. It isn't my best subject but i hope that doesn't stop me from one day becoming a data scientist.
You can always learn the math! It isn't anything beyond the normal college level courses
@@KenJee_ds Thank you! Do you think there’s any prepping I would be able to/ should do before college that can help me out? I’m gonna start learning how to code over the summer so I hope that’s helpful :)
@@Ashley-uh5lm You don't need to learn advanced maths in advance, but I recommend you to get really comfortable with functions (how their formula translates to their graphical form) and master basic arithmetic to be comfortable with exponents, logarithms, square roots and such things.
Trigonometry will be important to know for your math classes too, though not data science in general.
For reference, I was bad at math in highschool and had to properly learn these things during the first semester, adding me a ton of stress. Now I'm in the last year of my computer science undergraduate degree and plan to continue on to a Master's in DS or statistics.
I'm 6 months into junior DS role and God I am relieved to hear such things, make me not that disappointed in my job😅
Glad the vid helped to give you some additional perspective on the role! Congrats on landing the role though!
@@KenJee_ds thank you for your work and your words! We don't have any projects with ML, just a couple of linear optimizations - as you've said. A lot of software development though.
cool!!!!!!
Thanks for watching!
To help others out and save money I'd recommend do NOT go to college, get a few data related certificates. Start off as a entry level data analyst and while working utilize Udemy and YT on data science info.
After approximately 3-5 years as a data analyst apply to a data science job. Boom! Just saved you money. Any further details needed, just let me know.
Also, Google is your best friend. Learn how to use it being in the data world.
I don't know why ppl think going brick and mortar for school is still applicable. Go to brick and Mortar for Pre Med, Law, Finance, Accounting, Engineering.....tried and true professions but NOT Data Science!!!
What I looking for is Actually on Python SQL Tableau Power BI Job as what happen like my daily practice during learn data science, but I have no idea if the Job desc is variative
beginning today with learning R. let's see where i end up in a few months.
Awesome!
Been studying R for a month. Don't seem too bad just takes a lot of time to learn.
im an etl developer who does machine learning. literally spend most of my time scrubbing/cleaning/transforming data. derp
haha
My manager loves daily Stand-Ups... me on the other hand, not so much....
#TeamDataScience #PapayasIncToTheMoon 🚀🍈
I hear your project manager is a pretty wild guy. I'd love to meet him some day
@@KenJee_ds 😜I think I can make that happen
Hi Ken can I ask you if it’s true that data analysts are in more demand that data scientists?
Idk if eventually I just found a blog which supports more this position rather than data science roles.
As I knew Data analysts usually do things less advanced and let data scientists focus on more advanced things, but I suppose it depends on the location involved, on demographics (more or less people as candidates), on the field involved (tech, banks, manufacturers etc)
Could you make a video about “supply and demand dynamics on data science vs data analytics/analysis jobs?
I will definitely try to work in a video related to this! So the absolute number of data analyst jobs out there is higher than data scientist jobs. So I guess you could say that they are in more demand from a raw numbers perspective. I don't personally know how to quantify the demand on a per company level though. Since the data science salary is still significantly higher than that of a data analyst, it could be that the supply of qualified data scientists is still lower than what the demand calls for in that domain. Don't know if this helped haha, but that is how I would go about thinking about it!
Thank you very much I think I that are in more demand due to less advanced tasks like a Nurse advanced level and a doctor I assume
I spend 90% of my time as a data scientist on powerpoint...
lol I kinda do to (although I'm still doing consulting)
#TeamDataScience
Unrelated question. Can I ask what brand/type of glasses do you wear? I like that style
Warby parker! Working on trying to get a sponsorship so I can have some discount codes haha. Will update if that ever happens
Hi, i have an option to attend a course called "Optimization in data science" at my university (it's probably going to be very math oriented as I study math) and I wonder if that's something worth spending time on.
It sounds pretty interesting to me! Probably worth your time
11:01 was oddly relatable 😂
haha welcome to my life
Hello,
Are you able to get a sharpest minds mentor if you are at the beginning phase without any experience?
Nice video Ken!! I was watching some other related videos and saw that a good Data Scientist should work "independently", without needing to wait for orders from the boss.
What do you think about it? Does Kaggle helps with this "independency" and confidence to extract a lot of data and analyze it?
I think kaggle definitely can help with that!
kaggle is awesome.
I just came across your data science course on Skill up by simpililearn, I'll like to know, if I move on with this course, will it give me all the skills required as a data scientists? Or what are your recommendations
To the best of my knowledge, I don't have a course on there. Can you link it please
Now i am curious, do you ACTUALLY work 40 all hours a week as a data scientist? Or is that just a formality? I realise some times there is more work to do sometimes there is less, and so space for more free time. How does this work in the US?
Depends on the role. Most people do, I generally work either like 20 hours or like 60 haha
I am a Data Analyst, therefore I code a lot in SQL in any dialect. NoSQL is important as well
Very true!
As a People Analyst in a Telecommunications company, (doing both data analysis and data science) my work can be really different in just a couple hours haha
hahaha tell me a bout it!
Learning Sql. Can already do OOP with python and several languages. Should I learn R when I'm done?
I don't really know if there is a need to learn R unless you particularly want to do research
Hello, thanks so much for your video.
I want to use Data science in Cybersecurity, should I go through all the journey or what can you advice me? Thank you
I think there are some pretty good models you can use for anomaly detection. I don't see a reason to go through the whole data science path rather than just picking up a few tools for that domain
@@KenJee_ds ooh I see, thank you very much
So, the structure that you described sounds like agile methodology. Am I right?
hmm, I wouldn't quite describe it as completely agile but there are definitely similarities. It is highly iterative though!
btw the link in the bio isnt including your ref=kenjee, might want to change that so you get a comission
Thanks! I actually didn't do an affiliate campaign with them so it's nbd
9:30 What would be good questions to ask in an interview?
Older video, but these are some I generally recommend: ruclips.net/video/9-2OKLZfvbE/видео.html&ab_channel=KenJee
@@KenJee_ds Thanks, some of them I haven't thought of before!
I have an online data science test am nervous which site can assist with the tests
Interviewquery.com has some good stuff!
most of these apply for most engineering - and innovation driven jobs I think
I would agree!
I am actually looking for a data science job in biology...bioinformatics data science....can u suggest me any company
Awesome! I would check out the data professor's content around that. He works in bioinformatics
@@KenJee_ds thanks ken...I would like to tell you that I love watching your content....keep up the good work.
#TeamDataScience
Now I know better.
💪
Isn’t this like the millionth video you made with this same title ?
Lol only like the 2nd. It is different than the other one though (I think)
Data scientists love their jobs so much that they spend more time making videos about data science than data science...
haha just this one
What am I looking for In a data scientist job you ask?
Copy paste
lol
They mostly write 30 page long SQL queries that nobody can read or understand and then they sit back and play with their balls a lot because some idiot director is terrified of firing them and having to look at the 30 page long SQL queries themselves.
not wrong
That's soo true 😂 we had one of those and the whole department cried in pain after he left. Thousands of lines of sql queries for a product that we were still selling but now had no chance of updating
It is far more similar to a SAP Consultant job than I was thinking. The only difference is that the tools and the data you use as a data scientist aren't as predefined as an SAP Consultant which has it's pros and cons I guess. But for starters learning from 40 years of experience as best practices in SAP is invaluable, it not only holds the consultants hands but also the customers too so that when things get silly you can say that this is a standard for more than 40 years and they should do it 😂
yes haha!
Great video! But those ad hoc reports 😕
Thanks Austin! Those damn reports!
Data scientist can also be tasked with making pizzas.
Sorry for the repetitive joke lol.
Haha I love it! More pizza content coming soon
666 views, I will program as hell! 😈
lol
No words, just likessssssss!!! Do not waste another day > Promo`SM!!
NOTION HAS A DARK THEME???????? my life has been a lie, thanks for more insights into the data science world 🐢
Also early gang 🦾
It does in fact!
#TeamDataScience
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#TeamDataScience
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