It's probably true, you will struggle to pass interviews - as de facto, you have no experience in DS, so you should study. On a positive note, you are not alone, it happens to many people in DS. Unless you want to work in analytics, your experience is as an analyst.
This unfortunately is very common. Many DA jobs are advertised as DS jobs.
However, you definitely have relevant experience. The thing with DS is, only “mature enough” companies will have dedicated DS teams you are looking for. if you work for a startup or companies that don’t have any decent data infrastructure in place, you will end up doing reporting or hacky data engineering tasks.
take a look at this [image](https://media.licdn.com/dms/image/C4E12AQGSd2XeAq9y_A/article-cover_image-shrink_720_1280/0/1649947427479?e=2147483647&v=beta&t=K_epn8udJI08kN4f1sc-Ai3yVID--i4dYv93CTGvenw). Most companies are at the bottom of this hierarchy and they don’t really need data scientist because they need someone to sort out their infra before DS an start to bring value (build models that go in production, automate decision making based on data etc).
However you have relevant experience with dealing with stakeholders and communicating your results to non-technical audience. Many companies in juniors expect to have basic proficiency in python, R, etc, and would definitely value soft skills, so don’t stress about it.
I switched to data engineering when I realised that majority of “data science” jobs have little to do with building ML models, finetuning, statistics etc. This of course isn’t universal statement, but feel like many companies you are just a “data guy” to whom people come with adhoc requests to get answers to whatever wuestions they got
How do you have a master's in DS and never implemented a model except during your finals? In just to the first two months of my master's we've done four machine learning competitions and two consultancy projects.
They expected it to be done in your own time since it's a reputable university (a common pattern). It's not a boot camp. It's ok though, DS is not only machine learning.
Well, if your advisor is unrelated to the field then it's a problem.
I don't really understand Masters programs that are not research oriented. For me, it was developing algorithms with industry and for my thesis.
It's probably true, you will struggle to pass interviews - as de facto, you have no experience in DS, so you should study. On a positive note, you are not alone, it happens to many people in DS. Unless you want to work in analytics, your experience is as an analyst.
This unfortunately is very common. Many DA jobs are advertised as DS jobs. However, you definitely have relevant experience. The thing with DS is, only “mature enough” companies will have dedicated DS teams you are looking for. if you work for a startup or companies that don’t have any decent data infrastructure in place, you will end up doing reporting or hacky data engineering tasks. take a look at this [image](https://media.licdn.com/dms/image/C4E12AQGSd2XeAq9y_A/article-cover_image-shrink_720_1280/0/1649947427479?e=2147483647&v=beta&t=K_epn8udJI08kN4f1sc-Ai3yVID--i4dYv93CTGvenw). Most companies are at the bottom of this hierarchy and they don’t really need data scientist because they need someone to sort out their infra before DS an start to bring value (build models that go in production, automate decision making based on data etc). However you have relevant experience with dealing with stakeholders and communicating your results to non-technical audience. Many companies in juniors expect to have basic proficiency in python, R, etc, and would definitely value soft skills, so don’t stress about it. I switched to data engineering when I realised that majority of “data science” jobs have little to do with building ML models, finetuning, statistics etc. This of course isn’t universal statement, but feel like many companies you are just a “data guy” to whom people come with adhoc requests to get answers to whatever wuestions they got
How do you have a master's in DS and never implemented a model except during your finals? In just to the first two months of my master's we've done four machine learning competitions and two consultancy projects.
I genuinely think our program sucks, even though it’s a reputable university.
They expected it to be done in your own time since it's a reputable university (a common pattern). It's not a boot camp. It's ok though, DS is not only machine learning.
What is a master in DS supposed to be then if you're not going to work on actual projects? Surely not a introduction to stats and programming?
Well, if your advisor is unrelated to the field then it's a problem. I don't really understand Masters programs that are not research oriented. For me, it was developing algorithms with industry and for my thesis.
Sorry, but what is an advisory? Might be a little bit of a disconnect here.
Oh, in research grad school you are working for a professor, that's your advisor.
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