Book Image

Managing Data Science

By : Kirill Dubovikov
Book Image

Managing Data Science

By: Kirill Dubovikov

Overview of this book

Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis.
Table of Contents (18 chapters)
Free Chapter
Section 1: What is Data Science?
Section 2: Building and Sustaining a Team
Section 3: Managing Various Data Science Projects
Section 4: Creating a Development Infrastructure

Exploring data science team roles and their responsibilities

To complete a data science project, you will need a data scientist. Can a single expert lead a project? To answer this question, we can break down data science projects into stages and tasks that are, to some extent, present in all projects.

Before starting a project, you need an idea that will allow your client to achieve their goals and simplify their life. In business, you will look to improve key business processes within a company. Sometimes, the idea is already worked out, and you may start directly from implementation, but more often, your team will be the driver of the process. So, our ideal expert must be able to come up with an idea of a data science project that will provide value for the client.

Next, we will study two project examples to look at how simple projects can be handled with small teams or even...