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
1
Section 1: What is Data Science?
5
Section 2: Building and Sustaining a Team
9
Section 3: Managing Various Data Science Projects
14
Section 4: Creating a Development Infrastructure

Summary

In this chapter, we explored the complex topic of building and sustaining a team. First, we dived into the concept of team balance and looked at why it is crucial for a team's survival in the long term. Then, we learned about several leadership styles, including the situational leadership model and leadership by example. We then saw how we can create good task descriptions using the SMART criteria. We also mentioned empathy and active listening as the most important soft skills of a leader. We also explored the concepts of continuous learning and a growth mindset. Finally, we saw how a performance review process can help learning habits develop in your team.

This chapter concludes the Building and Sustaining a Team section of this book; congratulations on finishing it! The next section of this book will cover the topic of managing data science projects.

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