I was recently asked what I thought made for an effective data science team. Happily, I think my opinions on this topic are becoming more relevant, nuanced, and commercially valuable.
Two specific criteria I’ve recently thought of are:
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A nuanced understanding of software architecture patterns - what they are, why they’re relevant, what are strengths and weaknesses of popular solutions to common problems.
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The avoidance, or deliberate unlearning of programming practices that are learnt in academic (and to a lesser extent hobbyist) contexts.