Is it possible to transition into Core Data Science or ML roles without a PhD?

EY BL23
Jul 11 16 Comments

Current experience- Analytics/BI
YOE - 5

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TOP 16 Comments
  • Comcast dontdie
    Possible for SWEs, they bring strong sys design/devOps/DE skills to the table

    Very hard for “analytics/BI”. SQL/Tableau and python/R scripting doesn’t cut it chief. Everyone and their grandma is studying ML on coursera. Your competition is fierce.
    Jul 11 4
    • Axtria DesiLaunda
      So to get into core DS/ML, I need to become an swe first?
      Jul 11
    • Comcast dontdie
      You need SWE grade coding and sys design ability. Core ML positions are often in same org and pay grade as backend SWE. If they’re not, its an instant red flag
      Jul 11
    • Axtria DesiLaunda
      What do you mean by pay grade as backend swe? Can you provide the hierarchy of pay grades?
      Jul 11
    • Comcast dontdie
      Gross generalization here ymmv, but my broad understanding is thus:

      Analytics/BI/fake data scientist >> front end dev > backend dev/full stack/core ML
      Jul 11
  • New eeLf32
    Data Science is (already) redefined as glorified analytics/BI. That would be an easy transition for you. All of the analysts in my company literally got their titles changed to Data Scientists. There is a glut of talent in Applied or Research Science. Again, top talent is rare - but if you are self-learning you will be competing with new graduates who are more likely going to be better qualified and cheaper (you can get up there with tremendous amount of work but don't underestimate this) I feel doing ML implementation well is where the money is going to go next. Scaling ML implementation is super hard. If you have good sys design chops and can marry that will ML knowledge you will be in-demand.
    Jul 11 2
    • Axtria DesiLaunda
      How do you prove you have those skills?
      Jul 11
    • New eeLf32
      Depends on current role and what skills need to be proven based on self-taught knowledge. If you are SWE and need to prove ML knowledge, you can do hack-week type projects in current job that showcases your ML skills.
      Jul 11
  • This comment was deleted by original commenter.

    • EY BL23
      OP
      Did you also have SWE experience prior to your MS?
      Jul 11
    • New eeLf32
      Depends - if you built models on your laptop - then no. If you deployed a model at scale in production then likely yes.
      Jul 11
  • GE jjdndn
    The FAANG companies are building all the ML platforms which are self serving. The need for PHDs will eventually go down.
    Jul 11 3
    • Comcast dontdie
      Wrong. Demand for PhDs will stay strong to build innovative algorithms and compete on features. It’s the lower skillset infra/tooling that’s getting commoditized fast. Why build your own model deployment pipeline when you can pipe SQS into sagemaker and monitor it with cloudwatch
      Jul 11
    • GE jjdndn
      The same companies providing algorithms as a service
      Jul 11
    • Comcast dontdie
      Raw algorithm != functioning AI product
      Jul 11
  • Axtria DesiLaunda
    Start with a smaller company in the role you like, then move to reputed ones?
    Jul 11 1