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Be the Outlier : How to Ace Data Science Interviews

โœ Scribed by Shrilata Murthy


Publisher
New Degree Press
Year
2020
Tongue
English
Leaves
150
Category
Library

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โœฆ Synopsis


According to LinkedIn's third annual U.S. Emerging Jobs Report, the data scientist role is ranked third among the top-15 emerging jobs in the U.S. Though the field of data science has been exploding, there didn't appear to be a comprehensive resource to help data scientists navigate the interview process... until now.


In Be the Outlier: How to Ace Data Science Interviews, data scientist Shrilata Murthy covers all aspects of a data science interview in today's industry. Murthy combines her own experience in the job market with expert insight from data scientists with Google, Facebook, Amazon, NASA, Aetna, MBB & Big 4 consulting firms, and many more.


In this book, you'll learn...


  • the foundational knowledge that is key to any data science interview
  • the 100-Word Story framework for writing a stellar resume
  • what to expect from a variety of interview styles (take-home, presentation, case study, etc.), and
  • actionable ways to differentiate yourself from your peers.


By using real-world examples, practice questions, and sample interviews, Murthy has created an easy-to-follow guide that will help you crack any data science interview. After reading Be the Outlier, get ready to land your dream job in data science.

โœฆ Table of Contents


Introduction
Part 1 Getting Started
Chapter 1 What Is Data Science?
Chapter 2 What Is the Market Looking For?
Chapter 3 What Do You Want to Do?
Part 2 Cracking the Technical Rounds
Chapter 4 Modeling and Machine Learning Questions
Chapter 5 Probability, Statistics, and Experimental Design
Chapter 6 Programming Questions
Chapter 7 Case Questions
Part 3 Showcasing the Right Experience
Chapter 8 Tell Me about a Project You Worked On
Chapter 9 Presentation Interview
Chapter 10 Take-Home Exam
Chapter 11 Behavioral Interview
Part 4 Putting Your Best Foot Forward
Chapter 12 Crafting a Data Science Resume
Chapter 13 Data Science Portfolio
Part 5 Last but Not the Least
Chapter 14 Wrapping Up
Acknowledgments
Additional Resources
Appendix
About the Author


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