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Building Diverse Data Teams with Tracy Daniels, Head of Insights and Analytics at Truist

Tracy and Richie discuss the best way to approach DE & I in data teams and the positive outcomes of implementing DEI correctly.
· 49 min leggi
Tracy Daniels

Ospite

Tracy Daniels

Tracy Daniels is the Head of Insights and Analytics for Truist Financial Corporation. She leads the team responsible for Truist’s enterprise data capabilities, including strategy, governance, data platform delivery, client, master & reference data, and the centers of excellence for business intelligence visualization and artificial intelligence & machine learning. She is also the executive sponsor for Truist’s Enterprise Technology & Operations Diversity Council. Daniels joined Truist in 2018. She has more than 25 years of banking and technology experience leading high performing technology portfolio, development, infrastructure and global operations organizations.

Richie Cotton

Host

Richie Cotton

Richie helps individuals and organizations get better at using data and AI. He's been a data scientist since before it was called data science, and has written two books and created many DataCamp courses on the subject. He is a host of the DataFramed podcast, and runs DataCamp's webinar program.

Chat with AI Richie about every episode of DataFramed - all data champs welcome!

Key Quotes

To me, diversity is really about presence and representation, right? From different groups and perspectives and background. We talk about equity because we also want to think about fairness and justice. And then inclusion is really that environment that you create where are people feeling valued, heard, productive, seen. And I think all three of those really work together. One of the sayings that I really like, there's a... a woman by the name of Renee Mays, who was formerly the Chief Data Officer of Netflix. And she said, diversity was like being invited to the party, whereas inclusion was being asked to dance.

I think people should speak up and not be afraid to do that. I remember being part of a presentation just recently where the collateral was talking about heroes and data. And it was a wonderful lineup of diverse men, but it was all men. And I said, are there no women in this universe, you know, ecosystem that you and, you know, they just hadn't considered it. And so the second revision had more genders presented, right? So just speak up. I mean, there's very polite ways to say things you don't make me you don't need to make people feel horrible about themselves. But I think speaking up is important. I think advocate, as a senior leader, I try to make sure that I am talking about these issues and that I'm visible about these issues so that people understand it's important to me. If you're in the out group, you're not in the group being an advocate and an ally. So if you're a male, for women, if you're white for people of color, if you're cis, you know, you should advocate for our LGBT teammates as well.

Key Takeaways

  1. When hiring with DEI in mind, cast your net far to ensure you’re advertising to a range of people from a variety of backgrounds, be thoughtful when writing job descriptions to ensure they cater to the way different people think, and try to have a diverse hiring panel.

  2. It's essential to be aware of and actively mitigate biases in AI, especially when using training data. This involves checking for biases in data and ensuring representation of various groups.

  3. Implement frameworks that prioritize diversity and inclusion in the AI and data development process. This can involve participation metrics, access considerations, and regular reviews of representation in data.

Trascrizione

Richie Cotton: Welcome to DataFramed. This is Richie. Better data culture is something that every organization aspires to, because of course you want all your colleagues to be happy and productive when working with data. However, it can be hard to even define what a good data culture looks like, never mind setting up all the people and process initiatives to get there.

That means we spend a lot of time on this show and another day to count content. Trying to provide practical advice on how to deal with those devils in the details to improve your data culture. There's one area of data culture, namely diversity and inclusion, where I realize I've sometimes previously been a bit glib and said, of course you want to get better at diversity and inclusion without providing the advice to help you get there. Today we're going to rectify that and get into the nitty gritty of how to improve that important aspect of data culture. Our guest is Tracy Daniels, the Head of Insights and Analytics at Truist.

Tracy has two decades of experience managing teams at banks, having previously worked at Merrill Lynch and Bank of America. In addition to her management experience, Tracy is also the executive sponsor of Truist's Enterprise Technology and Operations Diversity Council. I'm looking forward to learning from Tracy. Hi, Tracy. Thanks for coming on the show.

Tracy Dan

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