5 Unusual Ways to Find your First or Next Data Science Job

You did all the right things:

getting a quantitative degree from a good university,
or doing some internship,
attending a few online classes (Coursera),
spent a few weeks on a valuable data science boot camp or our data science apprenticeship, working on real big data - especially automating data processes - even gained a certification (ours is cost-free, no exam required; it is based on your accomplishments),
followed these guidelines,
read data science job interview questions,
and read a few books (including ours which provide innovative, outside-of-the-box, modern content)

Now you are wondering, how do I reap the benefits? Here are five unusual ways to land a data science job: without having a resume, and without ever checking a single job ad. And once on the job, read 5 ways a data scientist can get fired.

Attend conferences, events or webinars. Talk to conference speakers: ask pertinent questions (not job related) and provide feedback about their talk. Even better: get invited as a speaker. Conference organizers are desperate to find quality speakers.
You can also create and organize some local events yourself, using Meetup. It's cheap and easy.
Publish. A book, an article, a chapter for an author (as long as your name is mentioned). Even better and easier: post blogs on community websites such as DSC, or with a traditional tech publisher. On DSC, you don't need to have experience writing blogs - all quality submissions are accepted, and you will reach the largest audience of analytics practitioners - many of them are also hiring managers, some are recruiters.
Work hard on your LinkedIn profile: ask colleagues for endorsements, mention awards, list articles, projects and presentations (Slideshare), write articles on LinkedIn Pulse, mention success stories on your profile. Add your skill list (see picture below).
Develop an interesting API, web or mobile app, and hope that it will be downloaded, or used by at least a few hundred people (it will sure get boosted if you talk about it on DSC). For instance, our intern developed a web app (API) that allows you to track the top data scientists to follow on Twitter, using AWS and Python, and later found a full time job in New York City. Another data scientist created an app that makes it very easy, with nice formatting, to navigate DSC on a mobile phone.

Add your skill list on LinkedIn, have your colleagues / boss / clients endorse it (and reciprocate!)

If in the short term you don't need money, you can also contact employers and offer to pay them to be accepted to work for them (in short, your hourly rate is negative). This makes sense only if you are looking to gain some specific experience (or work on specific data) that is hard to get outside the job in question. You are likely to experience a high rejection rate thought, worse than if asking a salary significantly above market rate. Another idea is to work remotely for overseas employers. Finally, there are ways to make money, as a data scientist, without working for an employer or a client. For instance, harvesting, summarizing and selling data or reports.

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Comment by Christian Kendall on November 4, 2016 at 9:03am: Pro bono consulting is an often under-rated way to get a feel for the kind of problems out there. Sometimes you'll be surprised at what people will approach you with (whether it's spit-balling or really impactful). You may even surprise yourself with what you can do given a bit of time to research and fiddle. There's no pressure in discover something is out of your league bc its no charge, and you can still help people out by referring them to next steps or other people and resources. If it turns out you can handle a question/problem that comes your way, then you can add that experience to your resume as a consulting project (and charge to do it next time:).

Comment by Lukasz Tracewski on February 8, 2016 at 12:27am: Here's a wild idea: find a cause you care about and engage with Non-Profit Organisation that does this. It's very likely they will have interesting data sets. Help them, help yourself. Practical experience that looks very interesting in your bio, gives you great flexibility in what and how you are doing it, allowing at the same time to publish your code. There is nothing I like more in a CV than a link to an open source repository.