9 The first months on the job

 

This chapter covers

  • What to expect in your first few weeks as a data scientist
  • How to become productive by building relationships and asking questions
  • What to do if you’re in a bad work environment

In this chapter, we’re going to walk you through what to expect in your first few months and how to use them to set yourself up for success. These months will have an outsize impact on how the job goes; this is your chance to set up a system and support network that will allow you to be successful. Although each data science job is different, some broad patterns and principles apply to any job.

When you start working, you’ll instinctively want to get as much done as possible. Fight that instinct. You need to be sure that you’re not just accomplishing tasks, but doing them in the right way. When you’re starting a job is the easiest time to ask questions about how something should be done, because you aren’t expected to know the processes at your new company. Managers occasionally forget that you don’t have the institutional knowledge that your predecessor may have had, so you might get tasked with something that doesn’t make sense to you. You might be able to fake your way through the first few tasks, but you’ll be much better served by asking questions early and finding out how to approach your work process.

9.1. The first month

9.1.1. Onboarding at a large organization: A well-oiled machine

9.1.2. Onboarding at a small company: What onboarding?

9.1.3. Understanding and setting expectations

9.1.4. Knowing your data

9.2. Becoming productive

9.2.1. Asking questions

9.2.2. Building relationships

9.3. If you’re the first data scientist

9.4. When the job isn’t what was promised

9.4.1. The work is terrible

9.4.2. The work environment is toxic

9.4.3. Deciding to leave

9.5. Interview with Jarvis Miller, data scientist at Spotify

Summary