Data Scientists, because of the versatility and range of their skills, can suffer from the paradox of choice when it comes to choosing a career. According to Barry Schwartz, a strategy for good decision-making when there is an abundance of choices will involve these steps, executed in a way that takes careful consideration of all the often unconscious biases (think Kahneman, Cialdini, and Thaler) we exhibit as a species:
- Figure out your goal or goals.
- Evaluate the importance of each goal.
- Array the options.
- Evaluate how likely each of the options is to meet your goals.
- Pick the winning option.
- Modify goals.
The following diagram shows two among many dimensions a data scientist should consider when trying to figure out their goals, and the career options that are available to them depending on where they land in terms of the importances of those goals.
And, as usual, life is often one big Multi-Armed Bandit problem, and there is a need to balance exploration and exploitation to get to where you ultimately want to be.