Learn about confirmation bias, hypothesis testing, the difference between data and software engineering, DataOps vs DevOps, the Dunning Kruger effect, and other topics.
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Today I speak with Humberto Stein Shiromoto, a senior data scientist at Telstra(*). We talk about doing science in a business context, the importance of being sceptical and to measure uncertainties, how to deal with failures and confirmation bias and the need to tell compelling data stories to promote positive change. Data science is not just software development with more data. We touch on the problem of changing data and how this affects models, the difference between DataOps and DevOps, the data mining lifecycle and the CRISP model, and hypothesis testing and the Dunning Kruger effect. Finally, we say when is a good idea to hire data scientists and when it isn't. You can follow Humberto on LinkedIn.
* Disclaimer: The views and opinions expressed in this episode do not necessarily reflect the official policy or position of the employer(s) or customer(s) of the speakers. Any content provided by the speakers are of their opinion and are not intended to malign any religion, ethnic group, club, organisation, company, individual or anyone or anything. The material presented in this episode is to ensure timely dissemination of scholarly and technical work.
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