Data Science Skills & Tools

New / Eng

New Eng

Aspiring ML Engr. / Data Scientist
Jul 22, 2017 15 Comments

These are the skills and tools needed by a data scientist that I can think of. Feel free to add or remove.

1. Excel
2. SQL
3. R
4. Python
5. Tableau
6. SAS
7. Presentation
8. Splunk
9. Power BI
10. Machine Learning


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TOP 15 Comments
  • New / Other

    New Other

    Data scientist
    Increasingly a lot of companies are using Looker as well
    Jul 29, 2017 0
  • Indeed / Product gsrDt45
    Many data scientists work on or very close to production systems. I'd add a basic level of computer science understanding and practical abilities to this list for many roles.
    Jul 22, 2017 0
  • Uber ywudi
    Should add specific Python packages like Pandas, numpy, matplotlib, sklearn, etc
    Jul 22, 2017 0
  • Adobe / Eng

    Adobe Eng

    Intuit, Autodesk
    Keep a left Sucker
    Jul 22, 2017 1
  • Apple took cim
    Don't data science folks need understanding of Machine Learning?
    Jul 22, 2017 2
    • Yahoo ItsTime
      I was thinking the same because thats what most of our data scientists do. Now i am wondering what do these people in other companies do. May be they r confusing data analyst/ data eng with scientists.

      P.S. I do all of that other people have mentioned but i am not a data scientist
      Jul 22, 2017
    • Apple took cim
      Same at Apple. A lot of DS people do machine learning.
      Jul 23, 2017
  • New rFEy10
    Splunk. Not a requirement but a good to know type of thing.
    Jul 22, 2017 1
    • New / Ops

      New Ops

      Splunk is on the way out. Sales are way down, check out LogRhythm though. very strong tool. lots of news on it.
      Jul 25, 2017
  • SAS / Consultant hihihello
    Using the tools listed above, data scientist need to develop all or some of the following skills:
    1. ETL of data
    2. Data mining / data massaging
    3. Data preparation (clean, validate, replace missing values)
    4. Data visualization & exploration (build visuals to understand high level relationships in your data
    5. Advanced analytical / statistical model building
    6. Predictive model building/machine learning model building
    7. Model building and comparison to select best model
    8. Deploy models/ put into production
    9. Manage & maintain models
    Dec 10, 2018 0
  • New / Eng

    New Eng

    Director, Software Engineer, machine learning
    Data cube is doing a good job of killing all these requirements
    Jul 25, 2017 0
  • I interviewed for DS position and was asked also/DS just like normal SDE so add also/DS as well.
    Jul 22, 2017 0
  • eBay gojilla
    Problem solving; Business understanding
    Jul 22, 2017 0


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