Data Science Blog | Data Science Leaders at Work

Analyzing Large P Small N Data - Examples from Microbiome

Guest Post by Bill Shannon, Co-Founder and Managing Partner of BioRankings Introduction High throughput screening technologies have been developed to...

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Evaluating Ray: Distributed Python for Massive Scalability

Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you...

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Themes and Conferences per Pacoid, Episode 12

Paco Nathan's latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data...

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Data Ethics: Contesting Truth and Rearranging Power

This Domino Data Science Field Note covers Chris Wiggins's recent data ethics seminar at Berkeley. The article focuses on 1) proposed frameworks for...

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Data Science at The New York Times

Chris Wiggins, Chief Data Scientist at The New York Times, presented "Data Science at the New York Times" at Rev. Wiggins advocated that data...

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Announcing Trial and Domino 3.5: Control Center for Data Science Leaders

Even the most sophisticated data science organizations struggle to keep track of their data science projects. Data science leaders want to know, at...

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Product Management for AI

Pete Skomoroch presented “Product Management for AI” at Rev. This post provides a distilled summary, video, and full transcript. Session Summary ...

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Machine Learning Product Management: Lessons Learned

This Domino Data Science Field Note covers Pete Skomoroch’s recent Strata London talk. It focuses on his ML product management insights and lessons...

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On Collaboration Between Data Science, Product, and Engineering Teams

Eugene Mandel, Head of Product at Superconductive Health, recently dropped by Domino HQ to candidly discuss cross-team collaboration within data...

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Themes and Conferences per Pacoid, Episode 6

In Paco Nathan's latest column, he explores the role of curiosity in data science work as well as Rev 2, an upcoming summit for data science leaders.

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Themes and Conferences per Pacoid, Episode 5

In Paco Nathan's latest column, he explores the theme of "learning data science" by diving into education programs, learning materials, educational...

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Data Science vs Engineering: Tension Points

This blog post provides highlights and a full written transcript from the panel, “Data Science Versus Engineering: Does It Really Have To Be This Way?

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Growing Data Scientists Into Manager Roles

In this post, Ricky Chachra, Research Science Manager at Lyft, provides insight for companies looking to home-grow their promising individual...

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Themes and Conferences per Pacoid, Episode 1

Introduction: New Monthly Series! Welcome to a new monthly series! I’ll summarize highlights from recent industry conferences, new open source...

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How data science can fail faster to leap ahead