8 Data Science Job and Career Skills

Published August 17, 2015 10:46 AM

|

Updated August 17, 2015 10:59 AM

1 Min Read

1. Basic Tools

No matter what type of company youre interviewing for, youre 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.

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 youre 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 youll 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 youre 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.

5. Data Munging

Often times, the data youre analyzing is going to be messy and difficult to work with. Because of this, its 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 youre 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. Youll be responsible for handling a lot of data logging, and potentially the development of data-driven products, says Holtz.

8. Thinking Like A Data Scientist

Companies want to see that youre a (data-driven) problem solver. That is, at some point during your interview process, youll 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. Its important to think about what things are important, and what things arent. 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. Visit additional Insurance Networking News slideshows here.