Slideshow 8 Data Science Job and Career Skills

  • August 09 2015, 3:04pm EDT
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8 Data Science Job and Career Skills

Whether you're a student or a business professional looking to make a career change, Airbnb's Dave Holtz says there are eight core competencies you'll need to succeed in the field of data science.

1. Basic Tools

“No matter what type of company you’re interviewing for, you’re likely going to be expected to know how to use the tools of the trade. This means a statistical programming language, like R or Python, and a database querying language like SQL,” Holtz says.

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2. Basic Statistics

“Statistics is important at all company types, but especially data-driven companies where the product is not data-focused and product stakeholders will depend on your help to make decisions and design / evaluate experiments,” Holtz says.

3. Machine Learning

“If you’re at a large company with huge amounts of data, or working at a company where the product itself is especially data-driven, it may be the case that you’ll want to be familiar with machine learning methods,” Holtz asserts.

4. Multivariable Calculus and Linear Algebra

“You may in fact be asked to derive some of the machine learning or statistics results you employ elsewhere in your interview. Even if you’re not, your interviewer may ask you some basic multivariable calculus or linear algebra questions, since they form the basis of a lot of these techniques,” says Holtz.

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5. Data Munging

“Often times, the data you’re analyzing is going to be messy and difficult to work with. Because of this, it’s really important to know how to deal with imperfections in data,” says Holtz.

6. Data Visualization & Communication

“Visualizing and communicating data is incredibly important, especially at young companies who are making data-driven decisions for the first time or companies where data scientists are viewed as people who help others make data-driven decisions,” asserts Holtz.

7. Software Engineering

“If you’re interviewing at a smaller company and are one of the first data science hires, it can be important to have a strong software engineering background. You’ll be responsible for handling a lot of data logging, and potentially the development of data-driven products,” says Holtz.

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8. Thinking Like A Data Scientist

“Companies want to see that you’re a (data-driven) problem solver. That is, at some point during your interview process, you’ll probably be asked about some high level problem – for example, about a test the company may want to run or a data-driven product it may want to develop. It’s important to think about what things are important, and what things aren’t. How should you, as the data scientist, interact with the engineers and product managers? What methods should you use? When do approximations make sense?” says Holtz.

Thanks and More

Dave Holtz is a data scientist at Airbnb. You can find additional insights about the eight data science skills in this complete blog written by Holtz. Also, visit additional Information Management slideshows here.