Ron SielinskiinTowards Data ScienceBeyond the NumbersHow confidence intervals can help focus attention and simplify analysisNov 9, 20221Nov 9, 20221
Ron SielinskiinData Science at MicrosoftStrategies for the data science interviewStatistical challenges are popular in data science interviews, but what do they tell us about people’s talent and their potential?Oct 12, 20212Oct 12, 20212
Ron SielinskiinData Science at MicrosoftCSAT: An emperor with no clothes?The simplicity of CSAT is deceptive. Too many companies trust the survey’s raw results, undermining efforts to drive real satisfaction.Apr 22, 20214Apr 22, 20214
Ron SielinskiinData Science at MicrosoftNo customer is averageThe simple average is rarely simple, but probability distributions and mixture models address the “typical” confusion.Feb 16, 20212Feb 16, 20212
Ron SielinskiinTowards Data ScienceBack to the future of data analysis: A tidy implementation of Tukey’s vacuumOne of John Tukey’s landmark papers contains a set of analysis techniques that have gone largely unnoticed, as if they’re hiding in plain…Aug 16, 20203Aug 16, 20203
Ron SielinskiinData Science at MicrosoftThe role of data scientist: A back-of-the-envelope modelAt Microsoft, we have over 2,300 people with “data scientist” in their titles. We all work for the same company in — ostensibly — similar…Aug 3, 20201Aug 3, 20201
Ron SielinskiinData Science at MicrosoftFostering excellence in data scienceOne challenge for data science teams is the ad hoc nature of our work. Presented with one-off problems, we tend to produce one-off…Mar 17, 2020Mar 17, 2020
Ron SielinskiinData Science at MicrosoftThe path to the cloudData science allows us to answer questions from the broadest possible perspective without sacrificing the fidelity of the individual…Jan 30, 2020Jan 30, 2020
Ron SielinskiinData Science at MicrosoftUsing Azure to understand AzureAt Microsoft, I run a data science team within Cloud + AI, the division that’s responsible for Azure, Visual Studio, Power BI, and more…Jan 9, 20202Jan 9, 20202