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Tereza Iofciu

Speaker

Tereza Iofciu

4

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Talks & appearances

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We talked about:

Tereza’s background Switching from an Individual Contributor to Lead Python Pizza and the pizza management metaphor Learning to figure things out on your own and how to receive feedback Tereza as a leadership coach Podcasts Tereza’s coaching framework (selling yourself vs bragging) The importance of retrospectives The importance of communication and active listening Convincing people you don’t have power over Building relationships and empathy Inclusive leadership

Links:

LinkedIn: https://www.linkedin.com/in/tereza-iofciu/ Twitter: https://twitter.com/terezaif Github: https://github.com/terezaif Website: https:// terezaiofciu.com

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Did you know that the Python Software Foundation Code of Conduct is turning 10 years old in 2023? It was voted in as they felt they were “unbalanced and not seeing the true spectrum of the greater community”. Why is that a big thing? Come to my talk and find out!

Data-driven products are becoming more and more ubiquitous. Humans build data-driven products. Humans are intrinsically biased. This bias goes into the data-driven products, confirming and amplifying the original bias. In this tutorial, you will learn how to identify your own -often unperceived- biases and reflect on and discuss the consequences of unchecked biases in Data Products.

We talked about:

DataTalks.Club intro Tereza’s background Working as a coach Identifying the mismatches between your needs and that of a company How to avoid misalignments Considering what’s mentioned in the job description, what isn’t, and why Diversity and culture of a company Lack of a salary in the job description Way of doing research about the company where you will potentially work How to avoid a mismatch with a company other than learning from your mistakes Before data, during data, after data (a company’s data maturity level) The company’s tech stack Finding Tereza online

Links: 

Decoding Data Science Job Descriptions (talk): https://www.youtube.com/watch?v=WAs9vSNTza8 Talk at ConnectForward: https://www.youtube.com/watch?v=WAs9vSNTza8 Slides: https://www.slideshare.net/terezaif/decoding-data-science-job-descriptions-250687704 Talk at DataLift: https://www.youtube.com/watch?v=pCtQ0szJiLA Slides: https://www.slideshare.net/terezaif/lessons-learned-from-hiring-and-retaining-data-practitioners

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html