What Does a Data Scientist Do?

What Does a Data Scientist Do?

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:

Big Data Podcast – What Is A Data Scientist?

What is a Data Scientist?

What is a Data Scientist?

If you want to do Big Data you need a Data Scientist.

Data scientists look for meaning and knowledge in the data. Advanced algorithms help data scientists visualize and look for patterns in the data.

“The data scientist is someone who has fantastic communication and empathy ability, as well a lot of mathematical skill, and then the engineering skill they need to do the math that they want to,” says Hilary Mason, Founder at Fast Forward Labs.

Considered one of the sexiest fields to pursue, the data scientist is now assisting companies of all shapes and sizes make sense of these massive data sets to better inform business outcomes.

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