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Do you have a PhD? If you do, it's going to help a lot with the transition. Skills for someone like you to work on - Python, the Python data ecosystem, machine

by jstx1 5y ago

Do you have a PhD? If you do, it's going to help a lot with the transition. Skills for someone like you to work on - Python, the Python data ecosystem, machine learning, deep learning, being a good software developer. Things not to worry about right now - Kubernetes, DevOps, cloud providers. You don't need JavaScript. Don't learn any Tableau/PowerBI and don't apply for jobs that require them unless you want a more analytics/business intelligence focused role. Or do learn them if you want to go in that direction but those jobs are quite different even if they have the same job title. (If a job description asks for TensorFlow/PyTorch and PowerBI/Tableau, it means that they have no idea what they're looking for whatsoever.) Maybe I should have started there - figure out if you want a more analytics/product/decision-making kind of role or more of an applied ML kind of role and then focus on that skillset. For the applied ML kind of data science job, you need the skills that I listed, for the other kind you need the stats background that you already have, some SQL, much less coding and a couple of BI tools.

te_chris 5y ago
This is very good advice. There's a world of difference between building and deploying models and doing BI.
trevormcneal 5y ago
Came here just to weight in for each and every point. This is the best answer so far. PhD is seem as a magical badge of super power, even if you can get a job without one, consider having it, is a 1.5x-2x salary multiplier.
- natalyarostova 5y ago
  Definitely not my experience in big tech data science. 30-50% of data scientists I work with don’t have a PhD, and took the self-taught hacker path, and earn just as much as PhDs. I probably earned a total of a million bucks by time I was as old as the average PhD data scientist hire out of academia.
- f00b4r_ 5y ago
  I've only seen PhD's increase salary for machine learning researcher positions. For ML eng, ML ops, and analytics, I haven't seen any pay differential. YMMV
  - deleted 5y ago
    [deleted]
edot 5y ago
Seconding this. Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”). Dashboards != analytics, but lots of companies seem to think they do. I would suggest looking at the Certified Analytics Professional certification from INFORMS. Operations Research is the original data science, and preparing for and passing the test is a good signal that you understand analytics. Machine learning is just one tool in the arsenal of providing value using data.
- gompertz 5y ago
  Sigh..another program that requires you to maintain your certificate by doing PDUs. This is like a 90s dark pattern that still creeps up from time to time. I can't get behind any organization that threatens to take education away from you.
- akhmatova 5y ago
  Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”). As opposed to a regression-and-printf monkey (sorry, "Data Scientist")? Like it or not - a lot of companies run on dashboards. To, you know, actually get their data out to people. So they can run their business, so you can get paid. If you dig math and like doing mathy things, good for you. There's no need to be snide about the work that others do that (like it or not) as just as essential to keeping the business afloat as yours. You are absolutely right though that pigeonholing in this industry is very much a thing. And intellectual honesty, not so much. Lesson being -- if one is targeting certain fields, it is often best to leave certain things off our resumes (or tone them way down).
  - gompertz 5y ago
    Well said. You need Tableau/PBI to tell the story of data, and distribute it to stakeholders. They aren't going to read a 10 page Word document of your findings... Maybe in 1999 they did. Looked at another way, you'd never publish a mathematical or statistical based thesis and not include any graphs or visuals. BI is just one of the steps after the analytics that is a necessary evil. It's not even a hard tool to use anyhow.

by jstx1 5y ago

te_chris 5y ago

This is very good advice. There's a world of difference between building and deploying models and doing BI.

trevormcneal 5y ago

Came here just to weight in for each and every point. This is the best answer so far. PhD is seem as a magical badge of super power, even if you can get a job without one, consider having it, is a 1.5x-2x salary multiplier.

natalyarostova 5y ago
Definitely not my experience in big tech data science. 30-50% of data scientists I work with don’t have a PhD, and took the self-taught hacker path, and earn just as much as PhDs. I probably earned a total of a million bucks by time I was as old as the average PhD data scientist hire out of academia.
f00b4r_ 5y ago
I've only seen PhD's increase salary for machine learning researcher positions. For ML eng, ML ops, and analytics, I haven't seen any pay differential. YMMV
- deleted 5y ago
  [deleted]

edot 5y ago

Seconding this. Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”). Dashboards != analytics, but lots of companies seem to think they do. I would suggest looking at the Certified Analytics Professional certification from INFORMS. Operations Research is the original data science, and preparing for and passing the test is a good signal that you understand analytics. Machine learning is just one tool in the arsenal of providing value using data.

gompertz 5y ago
Sigh..another program that requires you to maintain your certificate by doing PDUs. This is like a 90s dark pattern that still creeps up from time to time. I can't get behind any organization that threatens to take education away from you.
akhmatova 5y ago
Take Tableau off of your resume unless you want to be a dashboard monkey (sorry, “BI Developer”). As opposed to a regression-and-printf monkey (sorry, "Data Scientist")? Like it or not - a lot of companies run on dashboards. To, you know, actually get their data out to people. So they can run their business, so you can get paid. If you dig math and like doing mathy things, good for you. There's no need to be snide about the work that others do that (like it or not) as just as essential to keeping the business afloat as yours. You are absolutely right though that pigeonholing in this industry is very much a thing. And intellectual honesty, not so much. Lesson being -- if one is targeting certain fields, it is often best to leave certain things off our resumes (or tone them way down).
- gompertz 5y ago
  Well said. You need Tableau/PBI to tell the story of data, and distribute it to stakeholders. They aren't going to read a 10 page Word document of your findings... Maybe in 1999 they did. Looked at another way, you'd never publish a mathematical or statistical based thesis and not include any graphs or visuals. BI is just one of the steps after the analytics that is a necessary evil. It's not even a hard tool to use anyhow.