The oath of the data scientist

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I, (INSERT NAME HERE), being a data scientist of moral standing and noble intentions, do solemnly swear the following on pain of being banned from ever using a logistic regression again:

  • When faced with an individual untrained in advanced statistics or machine learning, I shall not belittle, condescend, or otherwise highlight my superior knowledge. I shall recognize that success comes from more paths than mathematics and look to simplify my work, no matter how painful it may be. I shall also remember this the next time my builder looks at me funny when I ask why my flashing needs to be replaced. Again.
  • I shall validate, re-validate, and re-re-validate all the data that I use, not just mathematically but logically. While it may be true that the data tells me I have customers over the age of eight hundred, I shall not trust it. Instead, I shall take the real world into account when examining my results before I share my findings. And, by doing so, I shall save myself from the inevitable embarrassment of trying to convince a hard-nosed marketer that they should target the ancient Egyptians in their upcoming campaign.
  • I shall always remember that my role is not to create interesting nuggets of knowledge. While this will stroke my ego and demonstrate my mental agility over my peers, it is unlikely to help my organization. Instead, my goal is to ensure my insights are acted on, thereby creating real value in some form. In the event I cannot or will not do this, I shall instead stand outside and gibber at the raccoons, deer, and other local wildlife, for this shall have as much impact on my organization’s bottom line. And, it's more fun.
  • Yea, though learning for learning's sake is a tempting seductress, I shall reject her. While I cannot predict what will be useful, I will always ensure that I actively look for ways to apply my research. Should I choose not to do so, I shall instead return to the terrors and tribulations of grant submissions within higher education.
  • My motto will be simplicity, not complexity; my crest execution, not theory; and my shield empiricism, not subjectivism. I shall always look for the most parsimonious, practical, and demonstrable solution, and if I cannot isolate the influence of my work on the outcome, I shall instead look for other opportunities to drive value. For if I cannot demonstrate the value of my work, who will?

Though we stand divided, united we shall transform the world's dark data into a better future. And though we exist in the dark ages, we strive for the enlightenment. I, (INSERT NAME HERE), will live, breathe, and otherwise model these principles, not just for me but for my wayward peers.

For if I do not, we shall be as doomed to irrelevancy as were the soothsayers of yore.

Delivering Business AnalyticsEvan Stubbs is the author of The Value of Business Analytics, a book that explains why teams fail or succeed. His most recent book, Delivering Business Analytics, explains the link between business analytics and competitive advantage, outlines the Data Scientist's Code (a series of management principles that move organizations towards best practice), and provides solutions to twenty-four common business analytics problems.

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About Author

Evan Stubbs

Chief Analytics Officer, Australia

Evan Stubbs is the Chief Analytics Officer for SAS Australia. He is the author of The Value of Business Analytics and Delivering Business Analytics, sits on the board member of Institute of Analytical Professionals of Australia, and is a guest lecturer at Macquarie University and the University of Sydney. He is a recognized expert in innovation and leads the Advisory business within SAS Australia, a group focused on transforming organisations into analytical competitors. His practical and experience-based talks on creating value through the use of business analytics are in high demand and feature regularly as keynote presentations.

1 Comment

  1. Hi Evan,

    Ok that is pretty funny. The builder and the flashing part made me LOL. Which is odd to do in a big room with only three people in it. Nicely done.

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