Rami Krispin | Building your Personal Brand in Data Science
21 September 2021, 05 pm

Rami Krispin | Building your Personal Brand in Data Science

Data Science Manager

Episode notes

Rami Krispin drops a ton of knowledge on topics including: why you should build a personal brand, how you should prioritize data science projects, and how you should communicate to senior leadership.

The Data Science Hangout is a weekly, free-to-join open conversation for current and aspiring data science leaders.

An accomplished leader in the space will join us each week and answer whatever questions the audience may have.

A few key snippets from our conversation:

01:45 - Start of session.
12:12 - Getting noticed by organizations - Branding yourself in data science.
23:00 - Why diverse teams help with problem-solving
31:10 - Communicating focus of a project to leadership
44:24 - Effectively scoping data science projects
53:21 - Sharing skills and techniques with team members

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Featured in this episode
Rachael Dempsey
Rachael DempseyHost
Community Manager at RStudio
I love connecting people across the data science community to share what they're accomplishing with data and help others do the same through community discussions, industry meetups, and more.
Rami Krispin
Rami KrispinGuest
Data Science Manager
Data science and engineering manager, and open source contributor. He is passionate about time series analysis, forecasting, and data visualization.

Frequently asked questions

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:


You don't have to register to join. You can add the event to your own calendar here:


There are three ways to ask questions during a live session:

  1. Raise your hand on Zoom and jump in the conversation live.
  2. Use the zoom chat.
  3. Use the slido link shared at the start of the call (can be anonymous)

All of the recordings from past sessions are shared here:


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?

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