Devoted Health and Data Science with Chris Albon
Play • 57 min

Michelle Casbon is back in the host seat with Mark Mirchandani this week as we talk data science with Devoted Health Director of Data Science, Chris Albon. Chris talks with us about what it takes to be a data scientist at Devoted Health and how Devoted Health and machine learning are advancing the healthcare field. Later, Chris talks about the future of Devoted Health and how they plan to grow. They’re hiring!

At Devoted Health, they emphasize knowledge, supporting a culture of not just machine learning but people learning as well. Questions are encouraged and assumptions are discouraged in a field where a tiny mistake can change the care a person receives. Because of this, their team members not only have a strong data science background, they also learn the specific nuances of the healthcare system in America, combined with knowledge of the legal and privacy regulations in that space.

How did Chris go from Political Science Ph.D. to non-profit data science wizard? Listen in to find out his storied past.

Chris Albon

Chris Albon is the Director of Data Science at Devoted Health, using data science and machine learning to help fix America’s health care system. Previously, he was Chief Data Scientist at the Kenyan startup BRCK, cofounded the anti-fake news company New Knowledge, created the data science podcast Partially Derivative, led the data team at the humanitarian non-profit Ushahidi’s, and was the director of the low-resource technology governance project at FrontlineSMS. Chris also wrote Machine Learning For Python Cookbook (O’Reilly 2018) and created Machine Learning Flashcards.

He earned a Ph.D. in Political Science from the University of California, Davis researching the quantitative impact of civil wars on health care systems. Chris earned a B.A. from the University of Miami, where he triple majored in political science, international studies, and religious studies.

Cool things of the week
  • How Itaú Unibanco built a CI/CD pipeline for ML using Kubeflow blog
  • Why TPUs are so high-performance
    • BFloat16: The secret to high performance on Cloud TPUs blog
    • TPU Codelabs site
    • Benchmarking TPU, GPU, and CPU Platforms for Deep Learning paper
  • Machine Learning Flashcards site
Interview
  • Devoted Health site
  • Devoted Health is hiring! site
  • Ushahidi site
  • FrontlineSMS site
  • New Knowledge site
  • Joel Grus: Fizz Buzz in TensorFlow site
  • Snowflake site
  • Periscope Data site
  • Airflow site
  • Kubernetes site
  • Chris Albon’s Website site
  • Partially Derivative podcast
  • Partially Derivative Back Episodes podcast
Question of the week

Chris Albon

To paraphrase: A computer program is said to learn if its performance at specific tasks improves with experience.

To find out more, including the definition of a partial derivative, buy a pack of Chris’s flashcards. Who knows, they might help you land your next job.

Where can you find us next?

Michelle is planning the ML for Developers track for QCon SF on Nov. 13.

Mark is staying in San Francisco and just launched two Beyond Your Bill videos: Organizing your GCP resources and Managing billing permissions.

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