2 Crafting your resume and narrative

This chapter covers

How recruiters parse resumes
Optimizing your resume to get interviews
Reframing your non-tech roles into relevant experience
Inducing fear of missing out (FOMO) in recruiters and employers
Speeding up the process using AI

Even if you are happy with your current resume, this chapter will show you how recruiters and hiring managers view your resume and how to ensure they don't ignore it. You wouldn't believe how many candidates I've met who described themselves as 'happy with their resume' but were leaving the most critical information off it. Within a week of reworking their resume, they started getting more interviews than they could take. No matter how experienced you are in data science, this chapter will help you get more interviews and qualify for more senior roles.

We'll see how to craft a resume that makes recruiters and hiring managers want to call you to begin the selection process. Whether you use a traditional, passive, or deep-and-focused approach, you’ll need to craft a resume, test its effectiveness, and improve it accordingly. In figure 2.1, you can see the iterative process to follow to improve your resume.

2.1 Resume as marketing collateral

2.2 Visibility

2.2.1 Resume structure

2.2.2 Title, employer, dates

2.2.3 The primacy effect

2.2.4 Countering conscious and unconscious bias

2.2.5 Deciding when to write more

2.3 Relevance

2.3.1 Title, employer, dates

2.3.2 Mining for relevant experience

2.4 Searchability

2.5 Fear of Missing Out (FOMO)

2.5.1 Workhorse signals

2.5.2 Value-added signals

2.5.3 Technical signals

2.5.4 Culture signals

2.5.5 How to use culture signals

2.6 Resume repositories and running experiments on your CV

2.6.1 Where should I post my resume?

2.6.2 When should I update my resume?

2.6.3 Running experiments with your resume

2.7 Your LinkedIn profile

2.8 Using LLMs and other tech to speed up resume creation, editing, and targeting