Fair to say that almost ten years after Harvard Business Review declared data scientist the sexiest job of the 21st century, many companies still don’t know how to build an effective data science team. One reason I joined The Mom Project to lead their data science team was that they had already established themselves asContinue reading “Building a full-stack data science team”
Before hiring a data scientist, consider building out a full ML pipeline with your existing data engineering and DevOps staff.
MLOps is a new and evolving area full of challenges and possibilities. It is new enough that it is unclear exactly what it will look like in a few years as more engineers and companies start to implement it.
Instead of delivering ML-powered guidance, many inexperienced businesses see their expensive data science efforts result only in PowerPoints.
AI expert Andrew Ng calls for data-centric AI/ML development, supported by better MLOps tools and processes. As an industry, we need to develop a machine learning development lifecycle that is as standard and effective as software development lifecycles.