Few questions: 1. In Drizzly, do you guys have the support of data engineers, or as data scientist you take up some data engineering work too? 2. Did you not use any SQL in Nielsen at all? Was that because there were so many specialized roles? 3. What are your pain points as data scientist? What things annoy you the most? 4. How does R being used by your fellow data scientists?
Hey! 1. We do have data engineers, but also use DBT so our analysts/data scientists can actually directly manipulate and add data to our production tables. So we do a bit of data engineering and are expected to learn our tech stack. 2. I did use SQL for sure, just not as complicated as now since we use SQL to add things to production tables so it has a higher standard of code. 3. Pain points is probably people expecting data scientists to be heads down. We know so much about the business because we build the forecasting and know where the business is headed - we should be expected to present more/work with leadership more and not be siloed and 'just' technical. :) 4. Not much R honestly, but it is used for MMM (Marketing Mix Modeling) at my company. I have only had to use it once for a couple days, but most of everything is python!
VERY INSIGHTFUL!!! Tf...first time I've seen someone be so eloquently open and descriptive about their role, I'm speechless. Please keep sharing, you are doing the God's work.
As an Economics and Math major, It seems as if companies look at science/quantitative majors; and throw us in research before trusting us with building or maintaining the models. Great video!
I have only just come across your channel! I love how you talk about data science. It helps to see where different pieces of knowledge/skills fit in the industry practice. Can't wait to break into the data science field. Wish me luck!! I'm really working on enhancing my skills and sending out applications.
Hi Priya. Thank you for sharing the different roles, responsibilities, and tech stack used. That was really useful as I'm preparing to apply to different data science roles. And yes the most likely solution is the simplest ML model because a more complex one can mean a strain on resources and overfitting by overtuning hyperparameters. It was interesting to see this principle applied to your business cases.
litreally i took Data Science course but i was confused how should i start but priya!!! t q so much for bringing this vedio so that we can relate ur experiences and we can learn alot best of luck for future!!!!
@@TheAlmostAstrophysicist I’m trying to break into data science and this is helpful helps me know what it would be like inside a company. I’m leaning more towards freelancing now
Thank you so much for talking about your experience. I'm breaking into this world of Data Science and even after about 3 monthts of learning now, I'm still overwhelmed about things I'm supposed to know or do. Your videos are such a comfort!
Could you do a video for the soft skills of ds? I'm unsure on how to improve on articulating ideas and delivery of insights to stakeholders in a SIMPLE (as my non technical teammates have emphasized) way 🙃
ABSOLUTELY. I am a big proponent of emphasizing communication and trying to think of better/succinct/easy ways of communicating my findings to stakeholders. I'll certainly add this to the list and made a video about it - communicating our work is just as important as building it out because no one would ever know how great it is if we can't explain it haha.
Watch out for your question inflection while speaking because it can hurt you professionally. This is when our voice rises at the end of our sentence. Also known as uptalk. Research has found that when the question inflection is accidentally used in a statement, it signals low confidence and insecurity . When the question inflection is used on a statement, it causes the listener’s brain to question the speaker’s credibility . The brain says, “If you aren’t confident in what you just said, why should I be?”
this is ONE DARN GOOD CAREER WALKTHROUGH. thanks a lot! you said the very first algorithm you wrote 'got deployed'. you didn't deploy it by yourself? I find deployment very complicated and .. scary((
Thank you for watching! I didn't deploy it myself, I shipped it to engineering and they did it on the backend in SQL. But I have built things in production later on and it really depends on the company tech stack, my current company's tech stack for production involves DBT and Snowflake and it makes everything so much easier!
This video is amazing thanks Priya! You really went into great details. Do you have any advice for someone who has just graduated with Data Science degree and wants to get into the field? (For example, on building good profile/portfolio, etc.)
I am Epidemiologist from another country and self-taught DS and Data Analysis. May be I have to go to get MS or boot camp?! Still can't find any job in US?
Hi Priya! Your energy is incredible and your career experiences inspire me a lot ☺️ There are so many videos I wanna see from you. Could you talk about the imposter syndrome when breaking into the field of DS? I feel like there are sooo many talented and smart people who started way earlier than I did in many fields of DS. Did you feel the same? 🥺 How to build confidence in this career? Also wanna hear about your experience of working at a big company vs a tech startup, which career path & progression is better? Thank you for sharing your experience and making great videos ❤️ lots of love ❤️
This means SO much to me, thank you!! 💛 I can certainly talk about those topics in future videos - I feel like I'm behind all. the. time. honestly but the best thing about data science is that there's always a continuous flow of data AND new methodologies that pop up so there will always be something original for you to do. It's really fun researching all that people have done in the past and experimenting on how to incorporate their work or even improve their work within your own projects. I absolutely love the suggestion about big company vs tech startup, I'm SUCH a startup person lol it's the best workplace ever. :) Looking forward to making videos based on your suggestions!
@@TheAlmostAstrophysicist Yes, always something new in DS! I feel like the imposter symptom is so real for people who are on the outsider, trying to break into the industry. Thank you for being so authentic and giving back to the community by sharing the perspective ❤️❤️❤️ can’t wait for your future vids 😊
hi Priya, I am fresher in the data science domain but had done my Ph.D. I have always been passionate about playing with data, lots of research work did in my Ph.D. I have completed my master's in data science. please can you give me suggestions for what essential skills need to be a data scientist. from the current demand of industries.
could you make a video answering some of the statements made by people who down data science. such as they say it is saturated. Tho tbh swe is saturated also at the junior level. But could you answer in video about whether it is true that many data scientists are just data analysts and the difference ? or also just if most data scientists have or do not have the skills needed for real data science
Video suggestion (maybe you’ve already done this!): you used a ton of words in this video that I didn’t understand 😅 (parts of your tech stack). It would be so helpful if you could do an explain like I’m 5 video where you explain how these different applications fit into your workflow as a data scientist and then link/group other similar ones. I think I am more intimidated by learning the tech ecosystem than I am by learning the actual technical skills 😅
Could you please describe or make another video about automating dashboards? Did you have to make real-time dashboards? I mostly process the production data in jupyter or vs code and then make dashboard on Power BI. But it is more of manual dashboard designing rather than automated dashboard update.
your videos are helpful... you are doing great.. I did my bachelors degree with specialization in computer science and statistics. I want to get into data science field so I started learning python ,SQL, power BI on Udemy. please suggest how can I get internship.
Glad I could help! If you're working on projects already, just add a projects section to your resume and add the most useful projects where you used a variety of tools (python data exploration, maybe an ML model, etc.) That'll showcase that you've used the skills you learned, and then everything after that is just applying!
Hi ma'am...there was a part you said you used gradient boosters to diagnose a dataset instead of manually looping through all of them..I didn't get that part ma'am..
Hello! I have been working as a web full-stack developer, now I'm thinking in changing to data science... I'm not sure if I would be good at it :( any advice ?
Hey! I do go in to the office 1-2 days a week now that I work at the Uber office. But prior to literally this month, from the start of covid until June 2023 I was fully remote.
![เปิดบ้าน โคตรสวย ป๋องกพล รู้จักตั้งนาน เพิ่งรู้ว่ารวย!!! l [Nickynachat]](http://i.ytimg.com/vi/tmgCF_2HfYI/mqdefault.jpg)
I'm finishing up the first year of my PhD in Psychology (Data Science minor) and you are bringing me so much hope!!!
That makes me so happy! Good luck with your PhD!
Few questions:
1. In Drizzly, do you guys have the support of data engineers, or as data scientist you take up some data engineering work too?
2. Did you not use any SQL in Nielsen at all? Was that because there were so many specialized roles?
3. What are your pain points as data scientist? What things annoy you the most?
4. How does R being used by your fellow data scientists?
Hey!
1. We do have data engineers, but also use DBT so our analysts/data scientists can actually directly manipulate and add data to our production tables. So we do a bit of data engineering and are expected to learn our tech stack.
2. I did use SQL for sure, just not as complicated as now since we use SQL to add things to production tables so it has a higher standard of code.
3. Pain points is probably people expecting data scientists to be heads down. We know so much about the business because we build the forecasting and know where the business is headed - we should be expected to present more/work with leadership more and not be siloed and 'just' technical. :)
4. Not much R honestly, but it is used for MMM (Marketing Mix Modeling) at my company. I have only had to use it once for a couple days, but most of everything is python!
VERY INSIGHTFUL!!! Tf...first time I've seen someone be so eloquently open and descriptive about their role, I'm speechless. Please keep sharing, you are doing the God's work.
This is so interesting! So cool to hear about the types of projects you could work on as a data scientist! You’re inspiring
HI TIYE 💛 You are inspiring!!!!
As an Economics and Math major, It seems as if companies look at science/quantitative majors; and throw us in research before trusting us with building or maintaining the models. Great video!
I have only just come across your channel! I love how you talk about data science. It helps to see where different pieces of knowledge/skills fit in the industry practice. Can't wait to break into the data science field. Wish me luck!! I'm really working on enhancing my skills and sending out applications.
Hi Priya. Thank you for sharing the different roles, responsibilities, and tech stack used. That was really useful as I'm preparing to apply to different data science roles. And yes the most likely solution is the simplest ML model because a more complex one can mean a strain on resources and overfitting by overtuning hyperparameters. It was interesting to see this principle applied to your business cases.
Awesome! Thanks so much for watching, good luck with your job search. :)
Hey Priya, great video!
Thanks so much, I appreciate it!! :)
Thank you so much for these videos Priya
Amazing!! Even though I don’t understand it.
😄😄😄
Best video explanation, thank you
litreally i took Data Science course but i was confused how should i start but priya!!! t q so much for bringing this vedio so that we can relate ur experiences and we can learn alot best of luck for future!!!!
Thank you so much!! I'm glad it's helpful, good luck with your Data Science career! :)
This channel is life!
Aww thank you!!
@@TheAlmostAstrophysicist I’m trying to break into data science and this is helpful helps me know what it would be like inside a company. I’m leaning more towards freelancing now
Thank you so much for talking about your experience. I'm breaking into this world of Data Science and even after about 3 monthts of learning now, I'm still overwhelmed about things I'm supposed to know or do. Your videos are such a comfort!
I'm new as well. I was going to start with SQL,Python and Tableau But I was thinking to begin my career as a Data Analyst.
this video is absolutely amazing!!!
You are very eloquent.enjoyed your video
Very insightful thanks
Could you do a video for the soft skills of ds? I'm unsure on how to improve on articulating ideas and delivery of insights to stakeholders in a SIMPLE (as my non technical teammates have emphasized) way 🙃
ABSOLUTELY. I am a big proponent of emphasizing communication and trying to think of better/succinct/easy ways of communicating my findings to stakeholders. I'll certainly add this to the list and made a video about it - communicating our work is just as important as building it out because no one would ever know how great it is if we can't explain it haha.
Watch out for your question inflection while speaking because it can hurt you professionally. This is when our voice rises at the end of our sentence. Also known as uptalk. Research has found that when the question inflection is accidentally used in a statement, it signals low confidence and insecurity . When the question inflection is used on a statement, it causes the listener’s brain to question the speaker’s credibility . The brain says, “If you aren’t confident in what you just said, why should I be?”
this is ONE DARN GOOD CAREER WALKTHROUGH. thanks a lot!
you said the very first algorithm you wrote 'got deployed'. you didn't deploy it by yourself? I find deployment very complicated and .. scary((
Thank you for watching! I didn't deploy it myself, I shipped it to engineering and they did it on the backend in SQL. But I have built things in production later on and it really depends on the company tech stack, my current company's tech stack for production involves DBT and Snowflake and it makes everything so much easier!
Good one!
Thank you!!!
Background music is very good i love it 💕
This video is amazing thanks Priya! You really went into great details. Do you have any advice for someone who has just graduated with Data Science degree and wants to get into the field? (For example, on building good profile/portfolio, etc.)
I am Epidemiologist from another country and self-taught DS and Data Analysis. May be I have to go to get MS or boot camp?! Still can't find any job in US?
Thanks 👍
Hi Priya! Your energy is incredible and your career experiences inspire me a lot ☺️ There are so many videos I wanna see from you. Could you talk about the imposter syndrome when breaking into the field of DS? I feel like there are sooo many talented and smart people who started way earlier than I did in many fields of DS. Did you feel the same? 🥺 How to build confidence in this career? Also wanna hear about your experience of working at a big company vs a tech startup, which career path & progression is better?
Thank you for sharing your experience and making great videos ❤️ lots of love ❤️
This means SO much to me, thank you!! 💛 I can certainly talk about those topics in future videos - I feel like I'm behind all. the. time. honestly but the best thing about data science is that there's always a continuous flow of data AND new methodologies that pop up so there will always be something original for you to do. It's really fun researching all that people have done in the past and experimenting on how to incorporate their work or even improve their work within your own projects. I absolutely love the suggestion about big company vs tech startup, I'm SUCH a startup person lol it's the best workplace ever. :) Looking forward to making videos based on your suggestions!
@@TheAlmostAstrophysicist Yes, always something new in DS! I feel like the imposter symptom is so real for people who are on the outsider, trying to break into the industry.
Thank you for being so authentic and giving back to the community by sharing the perspective ❤️❤️❤️ can’t wait for your future vids 😊
hi Priya, I am fresher in the data science domain but had done my Ph.D. I have always been passionate about playing with data, lots of research work did in my Ph.D. I have completed my master's in data science. please can you give me suggestions for what essential skills need to be a data scientist. from the current demand of industries.
Priya unga videos interesting ah iruku... Can you also share the common pitfalls that data scientists need to avoid?
could you make a video answering some of the statements made by people who down data science. such as they say it is saturated. Tho tbh swe is saturated also at the junior level. But could you answer in video about whether it is true that many data scientists are just data analysts and the difference ? or also just if most data scientists have or do not have the skills needed for real data science
Absolutely! Like a common data science misconceptions video? That sounds like a fun idea. Adding it to my list. :)
thank you
Video suggestion (maybe you’ve already done this!):
you used a ton of words in this video that I didn’t understand 😅 (parts of your tech stack). It would be so helpful if you could do an explain like I’m 5 video where you explain how these different applications fit into your workflow as a data scientist and then link/group other similar ones. I think I am more intimidated by learning the tech ecosystem than I am by learning the actual technical skills 😅
Could you please describe or make another video about automating dashboards? Did you have to make real-time dashboards? I mostly process the production data in jupyter or vs code and then make dashboard on Power BI. But it is more of manual dashboard designing rather than automated dashboard update.
your videos are helpful... you are doing great..
I did my bachelors degree with specialization in computer science and statistics.
I want to get into data science field so I started learning python ,SQL, power BI on Udemy.
please suggest how can I get internship.
Glad I could help! If you're working on projects already, just add a projects section to your resume and add the most useful projects where you used a variety of tools (python data exploration, maybe an ML model, etc.) That'll showcase that you've used the skills you learned, and then everything after that is just applying!
Hi ma'am...there was a part you said you used gradient boosters to diagnose a dataset instead of manually looping through all of them..I didn't get that part ma'am..
Wow I just realized how underqualified I am for a Data Scientist position haha
Hello! I have been working as a web full-stack developer, now I'm thinking in changing to data science... I'm not sure if I would be good at it :( any advice ?
I think you a lot more than you think
Do you always works from home?
Hey! I do go in to the office 1-2 days a week now that I work at the Uber office. But prior to literally this month, from the start of covid until June 2023 I was fully remote.
Juet listening to this made me remmeber why I hate computers 😂
You sound kewl
you are so cool🥹
🧠🦾💥🤍💣
Nise one:
Hey #savannahga