Автор: Roy Keyes
Издательство: Leanpub
Год: 2021-06-30
Страниц: 195
Язык: английский
Формат: pdf (true), mobi, epub
Размер: 10.3 MB
This book is designed to be a concise, opinionated, and practical guide to hiring the right data science technologists that your organization needs to achieve its goals. It will guide you through identifying the roles and skills your organization needs, how to source candidates, how to assess candidates, and how to help them succeed once hired. At each step, the book will try to give you a clear set of criteria and choices to create the most effective and efficient hiring process.
It's quite possible that the only thing more confusing than defining Data Science is actually hiring data scientists. Hiring Data Scientists and Machine Learning Engineers is a concise, practical guide to cut through the confusion. Whether you're the founder of a brand new startup, the senior vice president in charge of "digital transformation" at a global industrial company, the leader of a new analytics effort at a non-profit, or a junior manager of a Machine Learning team at a tech giant, this book will help walk you through the important questions you need to answer to determine what role and which skills you should hire for, how to source applicants, how to assess those applicants' skills, and how to set your new hires up for success. Special emphasis is placed on in-office vs remote hiring situations.
Data Science is as wonderful as it is ambiguous. If you ask ten data scientists what exactly Data Science is, you are likely to get ten answers different enough to leave you wondering if Data Science really exists as “a thing”. In the Chapter 2 we’ll cover some of the basic themes and common definitions behind Data Science, Machine Learning, and machine learning engineering. While you will not come away with the “one, true” definitions of these, hopefully you will feel that you have a better grasp of how these terms are used.
Among other things, Hiring Data Scientists and Machine Learning Engineers will help you:
Nail down your hiring needs
Write an effective job description
Work effectively with HR to source talent
Efficiently filter applicants
Conduct high signal interviews
Optimize your process for remote or on-site hires
Smell out DS BS
Who is this book for?
This book is aimed at anyone who wants to build or grow a Data Science or Machine Learning team. This may be the CEO of a small startup, a new manager at a large tech company, the leader of a new data-driven project at a non-profit, or the head of “digital transformation” at a massive global industrial company. While the needs and available resources across organizations vary greatly, this book aims to provide a useful framework and game plan adaptable to many different scenarios.
Different readers will come into this book with differing levels of experience related to hiring, Data Science, and Machine Learning engineering. Accordingly, some material can be skipped, depending on your background and experience. If you are a data scientist who has been through the hiring process on the candidate side of the table, you’ll understand a lot of the pitfalls and difficulties with data science skills and fit assessment, but may be unfamiliar with the logistics and challenges of the overall hiring process. If you have hired lots of people before, but have never hired a machine learning engineer, you’ll be familiar with the general hiring process, but may not have experience with the specifics of creating an MLE job description or what to look for in a candidate.
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