"Wanted: Data Scientist." You’ve learned the concepts, you've seen the six-figure salary estimates, and now you really want the job. But there’s a hurdle in the way: the job interview. Can you get one? And, once you land one, will you ace it or blow it?
This video covers the nuances, misconceptions, and realities of the data science job hiring process. Presented by a team of data science educators and job placement professionals, the video uses a series of mock interviews (the software engineering technical interview, the data science theory interview, and the applied data science interview) to explain the concepts you need to know, as well as the social and behavioral aspects necessary, to successfully navigate the data science interview process.
- Explore the distinctions between job titles like data scientist, data analyst, and data engineer
- Discover the "Growth Hacking" technique that will help you land interviews
- Understand who the stakeholders are in the hiring process
- Craft a "what-people-will-remember-about-you-after-the-interview" sales pitch
- Learn how to identify the data science concepts to review before the interview
- Review techniques for passing the technical screen and what to do if you flub a question
- Understand how to analyze salary vs. equity compensation offers
This video includes additional resources at http://www.galvanize.com/resources/the-data-scientists-guide-to-interviewing.
Jonathan Dinu and Katie Kent direct the data science program at Galvanize, Inc., a data science training organization. Galvanize has campuses in San Francisco, Seattle, Austin, Fort Collins, Boulder, and Denver.
Table of contents
- Preparing for Interviews
- Getting Interviews
- Real-World Experiences
- Mock Interviews
- Title: Cracking the Data Science Interview
- Release date: March 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491924259
You might also like
51+ hours of video instruction. Overview The professional programmer’s Deitel® video guide to Python development with …
Data Science Fundamentals Part 1: Learning Basic Concepts, Data Wrangling, and Databases with Python
20 Hours of Video Instruction Data Science Fundamentals LiveLessons teaches you the foundational concepts, theory, and …
Data Science Fundamentals Part 2: Machine Learning and Statistical Analysis
21+ Hours of Video Instruction Data Science Fundamentals Part II teaches you the foundational concepts, theory, …
Statistics for Data Science and Business Analysis
Statistics you need in the office: Descriptive and inferential statistics, hypothesis testing, and regression analysis About …