What are people’s stories about how to get a job as a data scientist? (or data analyst). This is a kind-of new career, and although quantitative background is obviously key, it’s not obvious how to get your foot in the door, if you haven’t done it.
I didn’t feel like I had my “foot in the door” when I applied, and got, data science jobs. For instance, I hadn’t done any data science projects and had only 1-2 related courses on my transcript. (To be fair, I was only applying for an internship and later converted to full-time, so perhaps that’s your answer?)
The old joke is that a data scientist is a better statistician than a programmer and a better programmer than a statistician. That’s what you need—statistics and programming. You don’t have to be world class in either, though it helps. You just need both.
I did not have a degree directly related to data science. I had studied political science and psychology, when most data scientists study statistics or computer science. (But both poli sci and psych do involve statistics.)
I had always been a hobbyist programmer, but I took time to learn R, which is a very common language for data scientists. (Python is also popular.) I did this through Coursera.
I had also learned Ruby, and I got my start as a software engineer intern after graduating college. I then transferred to the data science department.
Another big benefit for me was that the head of the data science department is a friend of mine, who also helped me get the internship. Skills matter, but so do internal referrals. ;)
It may have become more difficult. At my company, I believe we interview a lot more people for data science than we do Engineering. We seem to have a lot more difficulty finding engineers. That said, this could in part be because our data science seems more interesting than our engineering.
Software engineers do computer programming and are expected to know a lot about a programming language (stereotypically Ruby) and are not expected to know any math or statistics.
Data scientists are expected to both know how to program (typically Python or R) and to know a lot of statistics (and some math), but generally are not expected to know how to program nearly as well as software engineers.
Data engineers (my profession) are in the middle ground and are expected to know how to program just as well as a software engineer, just in a data-relevant language (typically Python or R). Data engineers are also expected to know some stats (much more than a software engineer) but not nearly as much stats as a data scientist.
What are people’s stories about how to get a job as a data scientist? (or data analyst). This is a kind-of new career, and although quantitative background is obviously key, it’s not obvious how to get your foot in the door, if you haven’t done it.
I didn’t feel like I had my “foot in the door” when I applied, and got, data science jobs. For instance, I hadn’t done any data science projects and had only 1-2 related courses on my transcript. (To be fair, I was only applying for an internship and later converted to full-time, so perhaps that’s your answer?)
Same here.
The old joke is that a data scientist is a better statistician than a programmer and a better programmer than a statistician. That’s what you need—statistics and programming. You don’t have to be world class in either, though it helps. You just need both.
I did not have a degree directly related to data science. I had studied political science and psychology, when most data scientists study statistics or computer science. (But both poli sci and psych do involve statistics.)
I had always been a hobbyist programmer, but I took time to learn R, which is a very common language for data scientists. (Python is also popular.) I did this through Coursera.
I had also learned Ruby, and I got my start as a software engineer intern after graduating college. I then transferred to the data science department.
Another big benefit for me was that the head of the data science department is a friend of mine, who also helped me get the internship. Skills matter, but so do internal referrals. ;)
It may have become more difficult. At my company, I believe we interview a lot more people for data science than we do Engineering. We seem to have a lot more difficulty finding engineers. That said, this could in part be because our data science seems more interesting than our engineering.
What is in your company the difference between data science and ‘engineering’?
Software engineers do computer programming and are expected to know a lot about a programming language (stereotypically Ruby) and are not expected to know any math or statistics.
Data scientists are expected to both know how to program (typically Python or R) and to know a lot of statistics (and some math), but generally are not expected to know how to program nearly as well as software engineers.
Data engineers (my profession) are in the middle ground and are expected to know how to program just as well as a software engineer, just in a data-relevant language (typically Python or R). Data engineers are also expected to know some stats (much more than a software engineer) but not nearly as much stats as a data scientist.