“A Compendium of Ancient and Modern Geography” — The British Library

Where Successful Data Scientists Sit

I often hear data science leaders pose this question:

Where should my data scientists sit?

  • Centralized: individuals are on a data science team, working with product teams on a per-project basis
  • Distributed: individuals are on different product/engineering teams

The stakes are high for getting this right — unhappy teams result in poor production, employee departure, and exacerbated difficulty recruiting. The conundrum reappears both in coffee meetings with new data science leads, on panels at conferences, and in my meetings with clients.

Neither model has proven inherently superior. LinkedIn has reorganized approximately every 9 months from one model to the other, and smaller companies move between the models as they grow. In practice there seems to be vast indecision — is the centralized or distributed model better?


In the distributed model, data scientists work on different teams, embedded with product and engineering. Because they spend their time with people in other functional roles, they collaborate less with other data scientists. Consequently, they duplicate methods, tools, workflows, and specific solutions of data scientists on other teams.

There are benefits and costs to both. If we’re aware of these tradeoffs, why are we racked with so much indecision?

Indecision is a Pattern

Why expand and contract?

Put simply, the role of the data scientist is to create access to data insights across the company. Be it predictive features of a risk model or test results for product variations, these insights create value for both the engineering team and the decisionmakers seeking to understand the future possible.

The Pulmonary Model

  • Monday, Friday with the data science team (Manager)
  • Tuesday, Wednesday, Thursday with a product/engineering team

Data insights are not only valuable within the product or business team in question, but laterally to other data scientists and upward to the business and its decisionmakers. Insights are oxygen — allow the company to breathe!

Where do your data scientists sit?

The Arctic, Maps, Data. @clarecorthell

The Arctic, Maps, Data. @clarecorthell