CAREER

Data Scientists

Overview

Salary Median (2020)

$98,230

Projected Job Growth (2019-2029)

+30.9% (much faster than the average)

Career

What Data Scientists Do

Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

How Leaders Describe a Typical Day at Work

Senior Director, Data Science ,

MINDBODY

I oversee the data science team that provides Customer Intelligence, Business Data Analytics and Business Intelligence to the entire organization. We combine our vast and unique data with advanced analytical methods and tools. The Data Science team makes sense of our data world through meaningful and actionable insights, identifying trends, delivering reports, informing product and infrastructure advancements, and promoting a culture of data-driven decision making.

Founder ,

Gayta Science

You can usually find me writing code to discover insights in data. With Gayta Science, I am typically asking an interesting question related to the LGBTQ+ experience, exploring data sources that could be used to shed light on the question, and then creating visuals and a narrative to communicate findings. In the past I’ve worked on both research and development teams, and a data scientist role can vary depending on the goal of a project. It is a broad field that you can shape your own path in.


Tasks & Responsibilities May Include

  • Analyze, manipulate, or process large sets of data using statistical software.
  • Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
  • Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
  • Clean and manipulate raw data using statistical software.
  • Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.

This page includes information from theO*NET 25.0 Databaseby the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under theCC BY 4.0license. O*NET® is a trademark of USDOL/ETA.