The easiest way to assess your own readiness is simply to start taking a look at real-world jobs and job descriptions. Do you have the skills that are listed there? Do you feel like you’d be able to do (or learn to do) the tasks described?
Your answer to these questions doesn’t have to be a rock-solid yes. Impostor syndrome is a real thing (here are some tips for combating it), and particularly for entry-level applicants searching for their first data science job are particularly susceptible to feeling it. It’s easy to look at an employer’s wish-list of skills and qualifications and intimidate yourself out of even applying.
When we talk to former Dataquest students with full-time jobs in data science, they regularly advise that other students apply for jobs even when they don’t feel ready. Amazon data scientist Caitlin Whitlock, for example, says she the prospect of her interview at Amazon was “terrifying.” But she still advises that aspiring data scientists “apply for any job, period. If you don’t think you’re going to get it, apply anyway.”
Miguel Couto, who got three job offers after applying for jobs on a whim, before he thought he was truly ready, agrees. That doesn’t mean you should go in unprepared—both of these students also said that they prepared really thoroughly for job interviews—but it does mean that you might be ready to get a data science job before you actually feel ready.
Learning data science skills can revolutionize your career. But unfortunately, great jobs don’t simply fall out of the sky as soon as you’ve mastered Python or R, SQL, and the other necessary technical skills. Finding a job takes time and effort. Finding the right job takes time, effort, and knowledge.
The goal of this career guide is to arm you with that knowledge, so you can spend your time efficiently and end up with the data science career you want.
The first step is figuring out what the career you want actually looks like. Where can your new data science skills take your career? Which path is right for you?
Answering these questions should be the first step in your data science job journey. And though the answers might seem obvious, it’s worth taking the time to probe deeper and really explore all of your potential options. That’s what we’ll be doing in this article.
Specifically, we’re going to take a look at some of the different job titles and descriptions that might be options for you if you’re looking to switch careers. We’ll also take a look at options you may not have thought about: going freelance and using data science in your current position.