5 Not So Obvious Ways to Get a Job in Data Science

This post was originally published on The Data Sleuth.

We've all been there before. You see a job on an aggregator site like Monster, Glassdoor, or Indeed that matches your interests and skillset. You fill out basic demographic information about yourself and upload your resume. Maybe you attach a general cover letter, maybe you don't. Who even reads those things anymore anyway, you wonder. You click the "Apply" button at the bottom of the screen and feel temporarily productive about the state of your job search and the acceleration of your career only to never hear back from the company - not even to acknowledge they've received your application. You do this about a hundred more times, expecting different results.

While unemployment is at the lowest since the beginning of the century as of the writing of this post, it still remains difficult to land a good job, even for an industry as hyped as Data Science. Hundreds, if not thousands, of candidates apply for a single job posting, many of whom have advanced degrees and years of professional and relevant job experience.

I used to think landing a job was just a numbers game, and if I only applied to enough postings, statistically speaking, I would eventually get an offer. During this shot-gun approach, I applied to over 20 jobs that were entry level data science jobs in a single day. I got exactly zero invitations for a phone screen, let alone an actual in-person interview. It was then that I decided to switch up my job search strategy because feeling productive is not always the same thing as actually generating solid leads. Here's a few of the strategies that I've used in my own job search that have connected me to real human beings who've had a genuine interest in speaking to me about a job that actually exists.

Slack Channels

Slack is a new platform launched in 2014 to to help facilitate communication among common interest user groups. For example, companies use Slack in lieu of email to track work projects and provide updates to relevant team members. I've used Slack during my 12-week Data Science course at General Assembly to follow along in lectures and ask questions of my instructor and classmates. My apartment building even has a Slack channel where residents receive building updates and invitations for get-togethers. Slack is user-friendly platform for people to connect - which means it can also be a way for job seekers to connect with hiring managers.

I've joined four Slack channels (apart from GA and my apartment building) that are focused exclusively on Data Science topics: two are focused on supporting women in Data Science, one is focused on the tech industry in New York, and the fourth is a private channel for Data Camp subscribers. Here are the Slack channels I've joined to stay connected to the Data Science community, and more specifically, to identify job opportunities:

wimlds (Women in Machine Learning and Data Science)

R-Ladies Community

NYCTech

Data Camp USA

Within each of these channels, there is a sub-channel dedicated to #jobs. Yes, employers actually post real jobs in these channels and usually include the email handles of hiring managers. It is not only ok but encouraged to email the poster directly to further inquire about opportunities that interest you. Congrats, you just connected to a real live human for a real live job.

My list is by no means an exhaustive one, and neither is this one. These are just some of the channels that are out there related to data. I would encourage you to do a little bit of research yourself to find a few Slack channels that would be good fits for you. When trying to identify Slack channels to join, consider your stack, your location, and your demographic. Connect with people who are similar to you and/or have similar interests. Get the emotional buy-in from someone who actually wants to read your cover letter/email instead of a hoping to be discovered.

Start a Blog

Every job hunter has a resume and a LinkedIn profile. For prospective employers, it can be difficult to actually gauge a candidate's technical ability based on self-reported bullet points, and women in particular underreport their abilities. To really give employers a better understanding of your skills, start detailing your analyses in a blog. This serves the twinned purpose of not only demonstrating your coding ability but also proving that you can actually present your findings in an organized way. Data Science is a multidisciplinary field in which practitioners can be expected to report their findings to a range of technical and non-technical stakeholders. Having the skills to communicate efficiently and methodically is just as important as slicing through a dataset with Pythonic prowess.

Moreover, having a blog demonstrates a deeper level of interest in data than the average applicant. I've even used my blog to supplement my skills pitch during interviews by inviting prospective employers to read through some of my posts. Multiple employers have actually followed up to tell me they read one of my posts, allowing me to stay connected to them long after I left their office.

Lunch Clubs

When I think of networking, I imagine a room full of people standing around awkwardly working the crowd to figure out who might be able to help them advance their agendas, whether it's to find a job, pitch an investor, or meet a potential co-founder. But without any structure, it can feel like a giant waste of time. When I meet up with someone in a professional setting, I like for both people to know why they are there and what the goal of the meeting is.

Lunch clubs like Lunchclub.ai and LetsLunch cut through the ambiguity by pairing people up with similar networking intentions. As a member, you state your role during the initial sign-up period, and upon acceptance to the club, you receive invites to meet up with people who can actually help you. Job seekers can pair up with prospective employers, start-ups can match with investors, and people who just want to connect with other professionals in their field can meet up one-on-one, too. And even if it's a total bust, at least you got to sit down and eat.

Hackathons

I recently went to a SexTech Hackathon in Brooklyn which focused on leveraging technology to improve the sex lives of 8 billion people. While I didn't have specific plans to break into the SexTech industry, it was a really great way to meet people from a variety of different backgrounds. Teams were self-selected, and I ended up on a team comprised of a "humanitarian" (soft skills), a "hipster" (design), a "hustler" (business savvy), and another "hacker" (coding) besides me. In just a day and a half, my team built a rudimentary chatbot decision tree in JavaScript (which I had never used before that weekend) designed to improve intimacy between couples. To me and the other hacker, it mattered not what our inputs were, whether they were NSFW-related or about flowers - the code and the logic was the same. And while I did go just to improve my coding skills and to do a fun, crazy thing in Brooklyn for a weekend, I actually ended up connecting with the other hacker on my team who ended up referring me for a gig with her part-time employer to tutor Python to kids aged 8-10. So really, you never know who you'll meet and how they might help you. Keep an open mind and sign up for any hackathon that looks like it could be fun. If nothing else, you'll have quite the story for Monday.

Cold email companies you admire

Companies post jobs on aggregator sites because they have an immediate need to fill. Looking at it in the negative, however, just because a company hasn't posted a job description that squarely aligns with your skillset doesn't mean there isn't a space (or funding) for you.

In a confusing age of both anonymity and oversharing, it can be difficult for employers (or anyone really) to get a read on someone without meeting them. Interviews will always be preferable, but second to meeting someone in person is writing them a sincere email. For companies that interest you, research the management team and identify someone you could write to. Keep it short and direct - no more than 4-5 sentences - to explain who you are, what about the company interests you, and what specific value you could add. For illustrative purposes, here's a sample email intro:

Hi Ms. Employer,

My name is Jess Chace, and I writing to you to inquire about a position with Data Science Co. DS Co. has been on my radar for several years now, and I've watched your growth and increasing number of tech solutions with great interest, especially (include specific example here). Having recently updated my own tech stack, I now feel competitive enough to join your team to help build out (whatever your stack can build here). Do you have time to meet up for an exploratory interview this week or next?

Looking forward to hearing from you,

Jess

Now, I'm not suggesting you try this technique on someone like Jeff Bezos or Andrew Ng. This strategy is more geared towards companies that are range from 10 to 1000 employees. Worst case scenario, you don't hear back from them. Best case scenario, you're invited in for an exploratory interview, bypassing the phone screen and getting straight to that face-to-face. More likely, however, is that you'll get a thank you for your interest or maybe even an invitation to check back in 3-6 months. Take them up on that offer. Check back in in 3-6 months, update them on what you've been up to since you last spoke, whether it's learning a new language or completing a new project. Think like a salesperson when it comes to advocating for your career: great job opportunities are like leads that need to be cultivated through months of check-ins and follow-ups. Play the long game.

Final Thoughts

No one is going to place a 150k salaried job in your lap because they recognized your technical aptitude and great cultural fit from your LinkedIn profile. Even if you have a degree from a fancy university with multiple years of professional experience, you are not owed a great job. You have to fight for it. When it's a numbers game like it is with the job search, and especially in a competitive field like Data Science, you have to think of ways to stand out from the crowd, because in reality, there are many candidates with similar qualifications.

The only way I've been able to get around that is to get the emotional buy-in of someone on the inside who can then advocate for you, whether it's writing an email to them, connecting over a private Slack channel, or meeting up with them individually. Otherwise, you're just another bag of words.

What about you? Have you had any success with these or other non-traditional job search techniques? Feel free to share them in the comments below!