Management on Harlan D. Harris

You Don't Need a Search Engineer; You Need a Search Scientist

harlan.harris@gmail.com (Harlan Harris) — Mon, 13 Apr 2026 00:00:00 +0000

Say you're an Engineering Manager or a Product Manager, responsible for a business-critical search system on a website. Maybe e-commerce, maybe a marketplace, maybe something else. Search is sort of working, it doesn't crash, and it's fast, but there's a feeling that "search isn't great", and you've been tasked with finding someone to help. Your first instinct, or that of your VP, might be some version of: “we need to hire a search engineer.”

How Search and AI Product Teams are Different

harlan.harris@gmail.com (Harlan Harris) — Tue, 03 Feb 2026 00:00:00 +0000

Engineering leadership knows the standard playbook for product teams: the Product Trio, the Spotify model, outcome-based roadmaps, and so on. I've seen teams adopt these practices and still struggle when they add responsibility for advanced algorithms -- search, recommendations, predictive modeling, or generative AI -- without changing how the team is led. The processes and role expectations that work for a typical product team break down when the domain is heavily algorithmic. This post pulls together what I've learned and what others have written about building teams that own these systems.

Staff Data Scientist: Comments on Will Larson's Staff Engineer Book

harlan.harris@gmail.com (Harlan Harris) — Fri, 27 May 2022 00:00:00 +0000

I recently read Will Larson's excellent book Staff Engineer: Leadership beyond the management track. Larson covers the individual contributor (IC, not management) roles that software engineers fill after they are promoted past Senior Software Engineer, with titles like Staff and Principal ("Staff-plus"). In the book, he synthesizes his own experience and the experiences of a number of other Staff-plus engineers, and provides great insights into how to get promoted to that level, and how to succeed at it. Great book -- you should read it.

Thoughts on Managing Data Science Team Workstreams (and a Shiny app)

harlan.harris@gmail.com (Harlan Harris) — Thu, 28 Jan 2016 00:00:00 +0000

This post was originally published on Medium

View this post on X (josh_wills)

There are different types of data scientists, with different backgrounds and career paths. With Sean Murphy and Marck Vaisman, I wrote an article about this for O’Reilly a few years back, based on survey research we’d done. Download a copy, if you haven’t read it. This idea is now pretty well established, but I want to talk about a related issue, which is that the type of workthat Data Science teams do varies a lot, and that managing those types of work can be an interesting challenge.

Building a Complementary Data Science Team

harlan.harris@gmail.com (Harlan Harris) — Mon, 23 Nov 2015 00:00:00 +0000

This post was originally published on Medium

I’m the Director of Data Science at EAB, a firm that provides best-practices research and enterprise software for colleges and universities. My team is responsible for the predictive models and other advanced analytics that are part of the Student Success Collaborative product that’s used by academic advisors and other campus leadership. We’re hiring data scientists, and I wanted to publicly say a few things about the roles we have advertised. (Note that EAB is part of a public company and is in a competitive market, so there are obviously things I’m not saying!)