Ask HN: What's the state of the job market in data science and machine learning?

Post by ywfs3370 » Sat, Dec 24, 2016, 10:17 AM UTC

shas3 wrote: post #36

rm999 wrote: post #23

Speaking for NYC, but I imagine silicon valley is similar. The supply-demand dynamics have changed a lot in the last couple years. I'd roughly break it out into two groups: people with work experience + strong software development skills, and those without. The first group is in higher demand than ever, and tend to add a lot of value to companies that really need it. The second group has gotten extremely crowded, esp…

Frankly, MOOC-type machine learning- being able to do plain vanilla logistic regression or black-box deep learning techniques is not enough to get a job. This knowledge and experience has to be paired with one or more strengths: excellence in programming, grad-level math/stat/numerical skills/theoretical machine learning, domain specific expertise or experience (e.g. vision, audio, natural language, networks, geophys…

Post by infinite8s » Tue, Dec 27, 2016, 8:55 PM UTC

user5994461 wrote: post #17

hardtke wrote: post #15

Earlier quoted context omitted.

Companies that have a research division and a separate engineering team to implement the research ideas are rarely successful. Anyone engineer good enough to do the implementation will figure out they can build something better without the input of the researchers. Microsoft and Yahoo both had great research teams whose ideas rarely saw the light of day.

I didn't say to put them in two separate divisions. Put both guys in the same place, working closely with each other. Any engineer will quickly figure out that he's out of his depth in the maths & statistics. Any mathematician will quickly figure out that he's out of his depth in the system building.

Post by infinite8s » Tue, Dec 27, 2016, 9:58 PM UTC

thearn4 wrote: post #66

TYPE_FASTER wrote: post #26

In my limited experience, there's a difference between a data scientist who can process data given data and a set of questions about it, and a data scientist who can figure out what data you need, and the questions that need to be answered. I think making the transition from the first role to the second role comes with experience, both with the toolsets, and thinking about the problem as a whole.

> data scientist who can figure out what data you need, and the questions that need to be answered. Isn't that describing a statistician?

Post by gallamine » Wed, Dec 28, 2016, 3:37 PM UTC

throw_away_777 wrote: post #125

From someone who is looking to transition to data science, the field is terrible if you haven't had an industry job before. I am ranked in the top 150 on Kaggle and can't even get phone interviews without someone in my network recommending me for a position.

Post by simonhughes22 » Wed, Dec 28, 2016, 5:12 PM UTC

simonhughes22 wrote: post #119

simonhughes22 wrote: post #65

I am the Chief Data Scientist of Dice.com. If you are interested in working as a junior Data Scientist, and are smart and hard working, please apply here: http://careeropportunities.dhigroupinc.com/ . The position is a telecommute role. We will absolutely consider people with no data science experience, so long as they demonstrate an aptitude for data science \ machine learning and can code.

For those with difficulties accessing the link, I apologize. I have notified HR, who maintain that aspect of the site. In the meantime, please email me your resumes to simon.hughes@dice.com