List of Hard Skills for Data Professionals

2020 list of desired hard skills for data professionals. From the most essential to the more difficult ones.

  1. The English language
  2. SQL
  3. Spreadsheets
  4. Descriptive Statistics (median, variance, correlation etc)
  5. Notions of Data visualization
  6. Notions of Time Series
  7. Handling computer files and folders (this one entered the list because we observed many people simply don’t have it)
  8. Notions of digital information storage (numbers and their limits, time, time zones, text, Unicode, compression)
  9. Probability
  10. Probability Distributions
  11. Linear and Logistic Regressions
  12. Python libraries ecosystem, pip, PyPi
  13. Python’s Pandas, DataFrame and Series wrangling
  14. Linux and the computer command line
  15. NoSQL, JSON, YAML, XML, SVG, APIs, HTTP, protocols and data representation
  16. Cloud and infrastructure as code
  17. Notions of symmetric and asymmetric cryptography, digital signatures and applications
  18. “Big data” systems (Hadoop, Spark)
  19. Software Engineering (classes, modularisation, versioning, containerisation, packaging, DevOps)
  20. Inferential Statistics (confidence intervals, hypothesis testing)
  21. Machine Learning algorithms for regression and classification
  22. Calculus and Numerical Calculus (integrals, derivaties)
  23. Natural Language Processing
  24. Computer vision
  25. Neural Networks

Please remember this list has only hard skills. Ethics, domain and industry knowledge, communication are very important soft skills that won’t fit in this list.

Generally speaking, beginning of the list is where Data Analysts are (up to ≈11). Data Engineers get up to the middle of list (up to ≈18). And Scientists get all the list.

There is also the following graph that I’ve produced:

data professions competencies

Leave a Reply

Your email address will not be published. Required fields are marked *