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Appendix A

Skills of a Data Scientist

This list builds on Joiner (1985) and Kenett and Thyregod (2006), mapping skills to the life
cycle introduced in Chapter 1.

General:
• Have a genuine desire to solve real problems and help others make sound decisions.
• Learn new computing environments and applications quickly.
• Be a good problem solver.
• Commit to, and meet, deadlines.
• Recognize and deal with your own personal biases.
• Recognize ethical issues and deal with them effectively (see Appendix D).
• When needed, have the courage to represent an unpopular point of view in an appropriate
way.

1. Problem elicitation:
• Help others formulate their problems and opportunities.
• Listen carefully and ask probing questions.
• Distinguish the important problems from those of lesser significance.
2. Goal formulation:
• Learn the problem domain and speak the domain language.
• Make good estimates of how much effort will be required to solve the problem.
• Meet decision‐makers regularly on their home ground.
• Network effectively.
3. Data collection:
• Participate in, or at least observe, data collection.

The Real Work of Data Science: Turning Data into Information, Better Decisions, and Stronger Organizations,
First Edition. Ron S. Kenett and Thomas C. Redman.
© 2019 Ron S. Kenett and Thomas C. Redman. Published 2019 by John Wiley & Sons Ltd.
Companion website: www.wiley.com/go/kenett-redman/datascience