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• Data infrastructure is sticky and difficult to move away from, so it's important to make the right decisions when building it
• The field of data science and machine learning can benefit from adopting software engineering principles
• Data scientists should be screened for coding skills and encouraged to code into the back-end code base
• Modular, testable, and simple systems are necessary for compounding interest in machine learning work
• The field of machine learning and AI has been heavily seeded from academia, which hasn't always used the best engineering practices