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The thing about scientific code is that it's often a potential dead end. The maintenance phase of the software life cycle is not as assured as it is in industry.

Writing good engineering software is not the scientist's goal so much as demonstrating that someone else with a greater tolerance for tedium (also someone better-paid) could write good engineering software.

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Exactly. I'd go further: in industry, the software is typically the end product, and the quality of the software is inherently relevant. In science, the output (the prediction of the simulation, the result of the analysis, etc.) is typically the end product, and the quality of the software is relevant only insofar as it affects the quality of the output.

In practice, of course, the quality of the software often does affect the quality of the output---but time spent on software quality creates less immediate value than it does in industry.

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