𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Data Science Careers, Training, and Hiring: A Comprehensive Guide to the Data Ecosystem: How to Build a Successful Data Science Career, Program, or Unit

✍ Scribed by Renata Rawlings-Goss


Publisher
Springer International Publishing
Year
2019
Tongue
English
Leaves
96
Series
SpringerBriefs in Computer Science
Edition
1st ed. 2019
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce.

Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data.

The book is divided into three sections, the first β€œBuilding Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second β€œBuilding Data Programs” is from the perspective of a newly forming data science degree or training program, and the third β€œBuilding Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations.

The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build.


✦ Table of Contents


Front Matter ....Pages i-xvii
Introduction (Renata Rawlings-Goss)....Pages 1-3
Building Data Careers (Renata Rawlings-Goss)....Pages 5-30
Building Data Programs (Renata Rawlings-Goss)....Pages 31-51
Building Data Talent and Workforce (Renata Rawlings-Goss)....Pages 53-66
Conclusion (Renata Rawlings-Goss)....Pages 67-68
Resources (Renata Rawlings-Goss)....Pages 69-85

✦ Subjects


Education; Technology and Digital Education; Engineering/Technology Education; Job Careers in Science and Engineering


πŸ“œ SIMILAR VOLUMES


Data Science Careers, Training, and Hiri
✍ Renata Rawlings-Goss πŸ“‚ Library πŸ“… 2019 πŸ› Springer 🌐 English

<p>This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, ac

Data Analysis and Machine Learning with
✍ Konrad Banachewicz πŸ“‚ Library πŸ“… 2021 πŸ› Packt Publishing - ebooks Account 🌐 English

<p><b>Get a step ahead of your competitors with a concise collection of smart data handling and modeling techniques</b></p><h4>Key Features</h4><ul><li>Learn how Kaggle works and how to make the most of competitions from two expert Kagglers</li><li>Sharpen your modeling skills with ensembling, featu

Build a Career in Data Science
✍ Emily Robinson, Jacqueline Nolis πŸ“‚ Library πŸ“… 2020 πŸ› Manning Publications 🌐 English

Summary You are going to need more than technical knowledge to succeed as a data scientist. <i>Build a Career in Data Science</i> teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the pr

Build a Career in Data Science
✍ Jacqueline Nolis, Emily Robinson πŸ“‚ Library πŸ“… 2020 πŸ› Manning Publications 🌐 English

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. About the technology What are the k

Executive Data Science: A Guide To Train
✍ Brian Caffo, Roger D. Peng, Jeffrey T. Leek πŸ“‚ Library πŸ“… 2018 πŸ› lulu.com 🌐 English

In this concise book you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You'll get a crash course in data science so that you'll be conversant in the field and understand your role as a leader. You'll

How To Start A Career In Data Science |
✍ Dr Briit πŸ“‚ Library 🌐 English

<p><span>All the information that you need to start a successful career in Data Science</span></p><p><span>Do you want to become a Data Scientist? Over half of all businesses are using data science to generate insights and value from big data. Data Scientist has been named as the No. 1 Best Job in t