Data Science Central blog pointed out an interesting discussion on Quora:
The blog post summaries the lengthy discussion on Quora as follows:
Here’s a summary of the very long and detailed top answer:
- Learn about matrix factorizations
- Learn about distributed computing
- Learn about statistical analysis
- Learn about optimization
- Learn about machine learning
- Learn about information retrieval
- Learn about signal detection and estimation
- Master algorithms and data structures
- Practice
- Study Engineering
All the numerous other answers go along the same lines. We strongly disagree with this – in the sense that these posters miss 50% of what makes a real data scientist: business acumen, domain expertize, craftsmanship and tricks of the trade, data vision (both metaphorically and literally), leadership, communication skills, vendor selection, consulting skills, and expertize in finding data sets (not just insights) and metrics. Also, I believe matrix factorizations and some other stuff (eigenvalues) are not part of modern data science anymore. These answers by young very smart educated people illustrate the mismatch between what hiring managers are looking for, and what potential hires think they should learn (reinforced by university curricula) to become a data scientist.
