What do experienced data scientists know that beginner data scientists don't know? Here is a quick overview.
- Automating tasks. Writing code that writes code.
- Outsourcing tasks to junior members or to consultants.
- Managing people, hiring the right people, managing managers who report to you.
- Training colleagues who might not be tech-savvy. Be an adviser for senior managers.
- Identifying the right tools and assessing the benefits and minuses of vendor software and platforms, for a specific large-scale project (construction of a huge taxonomy, etc.)
- Identifying the right algorithms and statistical techniques for a specific project. Blending these techniques as needed for optimal performance.
- Not trusting data; identifying useful external or internal data sources, blending various data sources while cleaning data redundancies and other data issues.
- Identifying the best features, perhaps using ratios or transforming, combining raw features to turn them into better predictors. Usually require a good understanding of the business you are in.
- Understanding executive talk, and translating executive requests, questions, concerns, or ideas into successful data science implementations.
- Measuring the ROI that you bring to your company; being able to convince executives about your added value (or providing sound explanations if ROI is negative or not perceived as positive, and offering a corrective path.)
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