What kind of topics do data scientist/engineers work on in corporates on a day to day basis

Intel
trident1

Go to company page Intel

trident1
May 8, 2020 3 Comments

What kind of topics do data scientist work on in corporates. Looking for broad areas:

For ex:

compnaies like Goldman, JP MORGAN is one category

Google Microsoft, apple etc. Are one category

I would like to know from your experiences what kind of problems arise and how is stats/quants/ML relevant to these from experience working on those topics

#tech #career

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TOP 3 Comments
  • PLAYSTUDIOS / Data
    GGMU40

    Go to company page PLAYSTUDIOS Data

    PRE
    HSBC, Discover Financial Services, Zoom
    GGMU40
    From my prior experience:
    Data Scientist:
    SAAS company — Customer churn & Retention, Product demand
    Fintech — Loan defaulters, Risk Modeling,
    Gaming — LTV, Customer Churn, Impact of gaming features on player behavior, playing pattern and monetization

    Data Engineer is bit broad area but involves build & maintain ML pipelines, Data Pipelines, Internal tools, Data Models, Reporting layers etc etc
    May 8, 2020 0
  • New
    TbTQ58

    New

    TbTQ58
    Four ml problems that will cover most industries
    - propensity to do something
    - churn(flipside retention)
    - life time value
    - recommendation

    Where you can make the above bespoke to the industry for example - churn for a subscription platform could be recast to churn for a account at a bank, client using your tools or whatever.

    Now specific models
    - fraud detection
    - document processing
    - etc

    There are obviously a wide range of models and use cases, but for a vast majority of the companies who are starting or part way through bring ML models the big 4 are the first to get buy in and potential bring the biggest chunk of improvement with the initial investment.

    7 yoe DS/Ml within various industries.
    May 8, 2020 0
  • Insurance companies will try to predict accidents
    May 8, 2020 0