Subject archive for "data-science-leaders," page 3

Data Science

Product Management for AI

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

By Ann Spencer36 min read

Data Science

Themes and Conferences per Pacoid, Episode 10

Co-chair Paco Nathan provides highlights of Rev 2, a data science leaders summit.

By Paco Nathan26 min read

Data Science

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 learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev.

By Ann Spencer8 min read


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 science. Mandel’s previous leadership roles within data engineering, product, and data science teams at multiple companies provides him with a unique perspective when identifying and addressing potential tension points.

By Ann Spencer35 min read

Data Science

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.

By Paco Nathan38 min read

Data Science

Reflections on the Data Science Platform Market

Before we get too far into 2019, I wanted to take a brief moment to reflect on some of the changes we’ve seen in the market. In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. This post describes our observations about these three segments and offers advice for folks evaluating products in this space.

By Nick Elprin8 min read

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