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Building a Culture of Experimentation to Speed Up Data-Driven Value

Posted Jul 05, 2022 | Views 732
# Culture of Experimentation
# Data-Driven Value
# Data-Driven Solutions
# HelloFresh
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speakers
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Delina Ivanova
Associate Director, Data @ HelloFresh

Delina has over 10 years of experience across data and analytics, consulting, and strategy with roles spanning financial services, public sector, and CPG industries. She is currently the Associate Director, Data & Insights at HelloFresh Canada where she leads a full-service data team, including data engineering, data science, and business intelligence and automation. She is also a Data Science and Machine Learning instructor in the professional development programs at the University of Toronto and the University of Waterloo.

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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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Vishnu Rachakonda
Data Scientist @ Firsthand

Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.

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SUMMARY

Supply chain/manufacturing are prime areas where the use of data science/analytics/ ML is underdeveloped, and experimentation is required to collect data and enable data-driven solutions.

This talk encourages companies to conduct experiments and collect data over time in order to build accurate/scalable data-driven solutions.

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