What makes someone a data scientist? This question keeps coming up continuously, so we’ve finally decided to write a blog to make it clear.
It is difficult to come up with one, single definition, because data scientists perform a wide variety of activities and have a wide variety of skills.
Typically, a data scientist can be best utilized working alongside an engineering and product management team to help develop products, and to help provide valuable insights to the business. Some data scientists will even refer to themselves as “data detectives.”
Here are some of the values/services/skills that a data scientist can provide:
- Product Analytics: To understand how users interact with the product through analysis of the logs
- Data Engineering / Data Pipeline: To automate data collection, aggregation, and visualization to produce metrics that are actionable
- Experimentation (A/B Testing): To establish causality that is otherwise too messy or not possible through observational study
- Data Modeling: To build predictive models
However, it is important to note that each of these is an individual skill and job. A single data scientist cannot perform all of these job positions.
Here is a great podcast where a data scientist explains in her own words what a data scientist is: