For those working in consulting as Data Scientists or AI/ML engineers — how much of your role actually involves advanced ML vs. simpler stats and a lot of data engineering? In my experience, most client needs are met without building complex models. Curious to hear how it is for others

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Data engineering 90% of the time. Clients’ data is often very messy and depending on the region can get unusable. Standard ML 8% of the time. And advanced 2% if you are the one pushing ( this is often not needed at most clients )

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