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Building Better Data Teams

Posted Aug 04, 2022 | Views 1.5K
# Data Teams
# Data Tooling
# RN Production
# Financial Times
# Ft.com
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Leanne Fitzpatrick
Director of Data Science @ Financial Times

Leanne is Director of Data Science at the Financial Times and is a passionate data leader with experience building and developing empowered data science and analytics teams in a variety of businesses. Leanne is in her element when developing and implementing strategic, technical, and cultural solutions to getting machine learning and data science into the operational ecosystem.

Leanne is an active part of the data and technology community, sharing innovation and insights to encourage best practices, from Manchester, UK to Austin, TX, and is an Advisory Panel Board Member. Outside of all things data you can ask Leanne about her golf swing (it’s not good - yet), her passion for American Football (specifically the Cincinnati Bengals), her latest sewing project, and her love for good music, food, and whisky.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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Mihail Eric
Co-founder @ Storia AI

Mihail is a co-CEO of Storia AI, an early-stage startup building an AI-powered creative assistant for video production. He has over a decade of experience researching and engineering AI systems at scale. Previously he built the first deep-learning dialogue systems at the Stanford NLP group. He was also a founding member of Amazon Alexa’s first special projects team where he built the organization’s earliest large language models. Mihail is a serial entrepreneur who previously founded Confetti AI, a machine-learning education company that he led until its acquisition in 2022.

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SUMMARY

We spent a lot of time talking about data tooling but we maybe spent not as much time talking about data organizations and efficiently running and organizing data teams.

What about starting with limitations instead of aspirations? Right constraints instead of the north star? In this session, let's learn more about a realistic take on the state of data organizations of today.

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