Data Science: Reality Doesn’t Meet Expectations

Dan Friedman:

I had high hopes about the potential impact of being a Data Scientist. I felt every company should be a “data company”. 

My expectations did not meet reality.

Where did my expectations come from? 

I attended a 12-week data science bootcamp in mid-2016. 11 of the 12 weeks’ focus were on machine learning (ML) and artificial intelligence (AI). At this time, ML & AI news mentions had hit an all-time high. Tesla was paving the way in self-driving cars, and even older behemoths like General Motors (GM) invested over a billion dollars in an AI company to stay at the frontier of automotive tech. At the consumer level, headphones emerged that used AI to automatically translate your words to someone else as you speak, and an AI beat the world’s best esports team.

I figured I’d spend most of my time buried in code and data to find hidden patterns, implement machine learning models in production and optimize them. Executives would likely rely on me to help inform the product roadmap based on insights in data, and I would be highly valued.

However, practically none of that happened.