4 ms·

I've had a few friends express interest in pivoting their domain knowledge + small programming knowledge into a Data Science job. Are there many success stories

by acbart 8y ago

I've had a few friends express interest in pivoting their domain knowledge + small programming knowledge into a Data Science job. Are there many success stories or guides out there for those who make such a transition? I went the formal route of getting the CS degree, so I never really thought about how you turn a non-CS degree into a CSy type job.

ThePhysicist 8y ago
Most data scientists I know don't have CS degrees but instead a background in physics, biology, math, economics or statistics. For a data science role focused around exploratory analysis, model building and idea generation (as opposed to a more engineering-focused data scientist) I'd say that a basic understanding of programming concepts and familiarity with the most essential tools (version control, Linux, Python/R) is probably enough to be accepted into a data science role. Data science degree programs are still quite novel so most companies don't expect to recruit people with such a degree, hence there are good opportunities for people with a STEM education I'd say.
- ekianjo 8y ago
  > Data science degree programs are still quite novel Indeed, plus you have zero business experience straight out of such a program so you are at a disadvantage if you are starting your career as such.
- bobmarley1 8y ago
  I've actually seen many many job postings looking for people with a PhD in Data Science which is truly mindblowing because there are only 2-3 such programs in the Country and most of them just started so none of their students are even on the job market yet.
  - PAClearner 8y ago
    ummm you are probably wrong. those job postings probably want people with PhDs in Computer Science/Statistics/Applied Math that did hard things with data.
SeanAppleby 8y ago
I have a degree in mechanical engineering and 2 years later am a software engineer pivoting into a datascience/dataengineering role after building an nlp product for our business. I only have my experience and don't know how repeatable it is, but I just got here by building stuff that I thought was interesting. Right at the end of college I tried to build a connected hardware/data harvesting startup, and it failed because I was a naive idiot who didn't understand just how hard the financials of building a hardware company were (all of the money up front for manufacturing runs) and how much time I would have to spend on things that I wasn't good at or really interested in, like building out supply chain and design for manufacturing or dealing with radio emission problems. But over that time I collected a couple of relevant awards (decently sized pitch contests, won at a mlh hackathon I did for fun etc.), built interesting prototypes of the hardware that worked and a web platform that supported it that people thought was interesting and that all worked as a hedge to show that I can at least build interesting things. So when I looked a recruiter came to me with a software engineering job at a startup that I thought was novel and interesting and I ended up taking it. Once I was there I saw a problem with a lot of labor going into dealing with relations between a bunch of types of texts, so I built a preliminary thing to automate as much of that as possible using relatively basic clustering and putting a person in the loop to collect labels so that I can come back and try something supervised later. The CEO brought on a chief data scientist to help me fix everything that I messed up and build a more scalable deployment pipeline and architecture for datascience microservices and now I work with him. But yeah, my experience is just that I built things and tried to make sure they worked and were sane, and then just showed people those things to convince them to let me do that for other things I wanted to do. I have a couple friends who did relatively similar things with pretty similar results.

by acbart 8y ago

ThePhysicist 8y ago

Most data scientists I know don't have CS degrees but instead a background in physics, biology, math, economics or statistics. For a data science role focused around exploratory analysis, model building and idea generation (as opposed to a more engineering-focused data scientist) I'd say that a basic understanding of programming concepts and familiarity with the most essential tools (version control, Linux, Python/R) is probably enough to be accepted into a data science role. Data science degree programs are still quite novel so most companies don't expect to recruit people with such a degree, hence there are good opportunities for people with a STEM education I'd say.

ekianjo 8y ago
> Data science degree programs are still quite novel Indeed, plus you have zero business experience straight out of such a program so you are at a disadvantage if you are starting your career as such.
bobmarley1 8y ago
I've actually seen many many job postings looking for people with a PhD in Data Science which is truly mindblowing because there are only 2-3 such programs in the Country and most of them just started so none of their students are even on the job market yet.
- PAClearner 8y ago
  ummm you are probably wrong. those job postings probably want people with PhDs in Computer Science/Statistics/Applied Math that did hard things with data.

SeanAppleby 8y ago

I have a degree in mechanical engineering and 2 years later am a software engineer pivoting into a datascience/dataengineering role after building an nlp product for our business. I only have my experience and don't know how repeatable it is, but I just got here by building stuff that I thought was interesting. Right at the end of college I tried to build a connected hardware/data harvesting startup, and it failed because I was a naive idiot who didn't understand just how hard the financials of building a hardware company were (all of the money up front for manufacturing runs) and how much time I would have to spend on things that I wasn't good at or really interested in, like building out supply chain and design for manufacturing or dealing with radio emission problems. But over that time I collected a couple of relevant awards (decently sized pitch contests, won at a mlh hackathon I did for fun etc.), built interesting prototypes of the hardware that worked and a web platform that supported it that people thought was interesting and that all worked as a hedge to show that I can at least build interesting things. So when I looked a recruiter came to me with a software engineering job at a startup that I thought was novel and interesting and I ended up taking it. Once I was there I saw a problem with a lot of labor going into dealing with relations between a bunch of types of texts, so I built a preliminary thing to automate as much of that as possible using relatively basic clustering and putting a person in the loop to collect labels so that I can come back and try something supervised later. The CEO brought on a chief data scientist to help me fix everything that I messed up and build a more scalable deployment pipeline and architecture for datascience microservices and now I work with him. But yeah, my experience is just that I built things and tried to make sure they worked and were sane, and then just showed people those things to convince them to let me do that for other things I wanted to do. I have a couple friends who did relatively similar things with pretty similar results.