Have you ever been asked to implement some crazy idea? To scratch your right ear with your left hand? To solve a problem which intuitively should not be solved as a data science problem? There are all kind of situations in which, as a data scientist, you may be asked to use your magic and find a solution for a problem that seems out of scope and very different from the problems you usually deal with. Whether those reasons are business constraints, customers demand, unavailable simple solutions, it all comes down to the same question: Would you accept the challenge?
In this talk we’ll explore a real-world challenge and try to answer some questions that all data scientists should ask themselves when facing a new problem:
- Does a “data science” approach make any sense for a certain problem?
- What other alternatives are available?
- How much time and resources should be spent?
- What is the accuracy level that a good solution should reach?