The First Step To Take When Looking For A Data Science Job
It's hard to know the right approach to use when looking for a data science job
You have decided to look for a new job in the data science field and are finding it very hard. As someone new to the field, it all looks very chaotic and confusing to you. You want to find the right job for you and don't want to waste your time trying to apply to every single company advertising a job. Sadly, all the advice you are getting seems to be do a bunch of things that appear to be disconnected and sometimes even contradictory - network, blog, take these 4 MOOC's, talk to recruiters, don't talk to recruiters, participate in Kaggle competitions, do a bootcamp, join a data science fellowship program, etc... Given a limited amount of time and wanting to find the right opportunity, where do you start?
The first step is to decide your "finding a job" strategy
The first step is to decide on your "finding a job" strategy. At a high level there are just three strategies to use when looking for a job: inbound, outbound, or a mixture of inbound and outbound. The way you go about finding a data science job will depend entirely on which strategy you choose to use. What's great is that by choosing a strategy you narrow the amount of things you need to learn, do, and communicate to potential employers. This makes it easier to focus on the process of "finding a job" as well as makes it easier to know when you're doing the right steps and when you're not leveraging your time in the best way.
The "inbound" finding a job strategy
The "inbound" strategy to finding a data science job is based on getting inbound interest from people interested in hiring you. The way to approach this strategy is to make your work and yourself as visible as possible. The goal of this strategy is to make it such that hiring managers and your potential peers will find your work, enjoy it, and reach out to you to see if you are interested in working for them. If you follow this strategy, you will spend the bulk of your time speaking at meetups / conferences, writing blog posts, and having an active profile on various data science forums and social networks.
The "outbound" finding a job strategy
The "outbound" strategy to finding a data science job is based on generating interest from people whom you have reached out personally. The way to approach this strategy is to seek out, find, contact, network with, and connect with as many people as possible in the data science community. The goal of this strategy is for you to find all of the hiring managers and potential peers as possible, befriend them, and convince them that they should hire you. If you follow this strategy, you will spend the bulk of your time attending meetups / conferences, having coffee meetings, doing "information interviews", and networking.
The combined "inbound" and "outbound" finding a job strategy
The combined "inbound" and "outbound" strategy to finding a data science job is based on getting people to reach out to you while at the same time reaching out to people personally. The goal of this strategy is to do both the "inbound" and "outbound" strategies simultaneously. Though this strategy takes a good deal of time and planning to make it work, this is the strategy that is most recommended by others and the one we recommend ourselves as well. By covering all of your bases and putting in the ground work both in showcasing yourself as a great potential hire as well as becoming a known part of the data science community, you will not only find and obtain a data science job faster and easier, you'll be able to create a more successful career.
The only wrong approach to use when looking for a data science job is to not choose a strategy
You want to find the right job for you and don't want to waste your time trying to apply to every single company or haphazardly trying a bunch of things like networking, blog, going through MOOC's, talking to recruiters, not talking to recruiters, participate in Kaggle competitions, do a bootcamp, join a data science fellowship program, etc... Given a limited amount of time and wanting to find the right opportunity, you need to start off on the right path.
The way to do this is to decide on your "finding a job" strategy: "inbound", "outbound", or a "combination of inbound and outbound". Once you have chosen a strategy, the way you go about finding a data science job will then depend entirely on which strategy you chose to follow. What's great about taking this as your first step is that you narrow the amount of things you need to learn, do, and communicate to potential employers.
So have a think of which strategy sounds more appealing to you and decide which strategy you will use to find a data science job. Good luck!