Merav Yuravlivker, CEO of Data Society, describes how to get people excited about data science internally. Also, how data science teams should think about defining and measuring success.
Data Society is a leading provider of customized data science training programs and AI/ML solutions for enterprise and government agencies (datasociety.com)
A few key snippets from our conversation:
01:13 - Start of session
7:33 - Ways to get people invested in data science internally
13:00 - Measuring and defining success with data science projects
15:50 - Growing engagement at internal community events / lunch & learns
32:38 - Building to serving predictive models
47:47 - Calming fears around the company "being behind" in using data
58:50 - Doing both the A & B of A/B Testing
An audience-led conversation held on Zoom focused on data science leadership that is open to all every Thursday at 12 ET. You can check out the recordings on this site as well! Learn more on the About DSH page here:https://www.rstudio.com/data-science-hangout/about
You don't have to register to join. You can add the event to your own calendar here:https://www.addevent.com/event/Qv9211919
There are three ways to ask questions during a live session:
All of the recordings from past sessions are shared here:https://www.rstudio.com/data-science-hangout/live-calls
That's up to you. The host, Rachael usually opens up the discussion by asking the featured leader what they are most excited about in data science currently, and then we turn the questions over to the audience. Here are a few examples of questions that have come up before:
What is the divide between a business analyst and a data scientist?
What is the most unique problem you've had to solve in your industry?
My leaders refer to our BI tools when asked about data science, do you consider BI data science? Why/why not?
Did you always have managing skills/people skills, or did you have to learn them?
Could you define levels of data science maturity for companies?