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Opinion
Data Scientists: Problem Solvers First, Algorithm Wizards Second
Having a hammer and seeing everything as a nail
Recently, I had an opportunity to meet with a data science team from a large government agency in Australia. From what I could tell, the team consisted of highly skilled individuals in data science and machine learning. However, during our conversation, I couldn’t help but notice a common theme among the data scientists. They seemed more interested in discussing the latest algorithms to predict human behavior rather than discussing and defining the core problems they were trying to solve.
This experience highlights a common issue I see in the world of data science: the tendency to see everything as a data science problem. It’s like having a hammer and seeing everything as a nail. While algorithms and advanced techniques can be powerful tools, it’s essential to remember that data scientists should be problem solvers first and foremost.
In this article, I intend to shed some light on the importance of problem-solving skills in data science and why they should be prioritized over algorithmic techniques. I will also discuss why it’s critical to understand organizational readiness when proposing data science solutions and how data scientists can lead their organizations…