As with any role/skillset, the explosion of data science demand has lead to an explosion of "data scientist" supply. When demand was greatly exceeding supply, y

As with any role/skillset, the explosion of data science demand has lead to an explosion of "data scientist" supply. When demand was greatly exceeding supply, you naturally saw the definition and requirements of data science roles loosening. When I contact companies about DS roles, I like to ask what they mean by "data science". Often times you would find roles that were some mix of: SQL analyst (no DB admin skills required), Python hacker (no "real" software eng skills required), and basic stats (can you calculate a confidence interval?). What I've seen in more recent years with growing supply and maturation of departments is the need for specialization. Can you do hardcore statistics? Are you an ML practitioner? Are you a data architect? Basically, the blended role DS hacker is more commonly (and correctly IMO) relegated to a various analytical and strategy roles. Honestly you haven't missed the boat and you don't need a formal education, but I would highly recommend having a depth of skills in one or more areas of data science generally with an example or two to back it up. Basic skills are just table stakes at this point.