If you’ve ever sent resumes into the black hole of the depersonalized job market, you’ve likely thought: There’s got to be a better way of doing this.
Have you considered the hidden job market?
The hidden job market refers to jobs that are out there but are, for one reason or another, not posted publicly. Tapping into it requires a strategic, proactive effort to reach out and build relationships with the right people at the right companies.
For data scientists, the hidden job market is a particularly valuable resource to tap into. The need for data science professionals is growing so quickly that there are job opportunities that haven’t been posted yet. And the rapidly evolving nature of the data science field means your skills might meet needs companies don’t even realize they have yet, meaning jobs could be created for you.
How Data Scientists Can Tap Into the Hidden Job Market
- Identify companies that are likely to grow. Start by looking at startups that top venture capital firms are investing in. Those are likely to be hiring now or in the near future.
- Reach out to target companies. Start a conversation, via email or phone, and build a relationship with hiring managers or team leads. When new positions open up, they might think of you. Or, you could inspire companies to create a role that matches your skill set and fulfills a new need.
Data Science’s Relationship With the Hidden Job Market
The reasons why a specific job might be hidden are many, but there tend to be three main categories of these jobs, according to Ed Samuel, executive career and life coach at SamNova, a career coaching firm.
The first is when someone at a company is going to be let go and the effort to replace them is being kept quiet. The second is when a company is growing and job postings haven’t been made public yet, even if hiring managers or team leads know the need exists and plan to post jobs. And the third is when a company has an unmet need and might be willing to create a position for the right person.
Data science professionals are uniquely positioned to capitalize on both the second and third categories. Growth is part of the world of data. Demand for data scientists is growing much faster than in other fields. This demand, in addition to data science’s tendency to morph and adapt rapidly, means there is a lot of potential for positions to be created for data science professionals.
“I think the more fluid the industry, and if it’s evolving and changing like data science, then there’s more of an opportunity to create a job where that problem or need matches the skill set that someone’s presenting,” said Samuel. “And the more rigid and traditionally structured an opening is, it becomes a little bit less easy to create a role from scratch.”
While this can be a headache during job hunting, Nick Singh, co-author of Ace the Data Science Interview, described it also as a benefit to professionals in the field trying to tap into the hidden job market.
“There’s a lot of leeway between the data science roles in the sense that a machine learning engineer could do the job of data scientists, who could do the job of data analysts,” he said. “Whatever the job description is, if the company’s really looking for talent, you’ll find a way in.”
Identify Companies Poised for Growth
But before you find a way into a specific position, you need to identify companies you want to get into. And these should be companies that are — or will be — looking for talent. For this, Singh recommends looking into unicorns.
Specifically, he urged data science professionals to go after maturing startups at the series B or series C funding levels. Such startups, by virtue of having gotten past the seed stage and series A funding, have proven they are delivering a return on earlier investments enough to warrant more and keep growing, Singh said. Basically, if a startup is growing, you know they are likely to be hiring, either now or in the future, making them a good company to target for your hidden job market efforts.
“In a startup that’s growing fast, your own opportunities for career advancement are way bigger,” he said. “For folks who are really trying to move up in their career — especially early career people who are ready to do the work — it is a very good bet to be betting on these series B, series C startups that have some funding, some stability, but still a lot of upside left.”
When it comes to identifying those companies, what better way than to take a cue from those groups that professionally bet on which particular startups will become unicorns? Singh suggested data science professionals keep tabs on what top venture capital firms like Andreessen Horowitz and Sequoia Capital are funding.
Some practical ways of keeping up with the funding activities of VC firms include setting up Google news alerts for related search terms like “series B” and VC firm names. You could also follow VC firms’ social media accounts or sign up for their newsletters. Consider also regularly visiting or signing up for the newsletters of outlets that regularly report on startup funding news like Crunchbase, TechCrunch and Built In.
If those top venture capital firms are betting on a startup with series B or series C funding, job seekers can assume “these companies are going to grow, that they’re well funded, that they’re going to have an easier time accessing the capital markets later on,” said Singh. This likely translates into a mix of stability and growth opportunities.
Reach Out and Start a Conversation
Once you’ve found growing companies that look like good prospects, tapping into that portion of the hidden job market takes being proactive and starting a conversation with the right people at your target companies.
For Samuel, the best way to do that is to make a phone call to the hiring manager or data science team leads. He advised against calling up target companies and starting with something like “I’m calling about a job.” Such a conversation is “dead on arrival,” Samuel said. Instead, the goal is to start a conversation — not necessarily a long one — and introduce yourself to the person.
“Your job is to give that person a mini-introduction as to who you are, your professional years of experience, something of value that you have done that might resonate and let them know you wanted to spend a few minutes to network with them,” he said.
The ultimate goal is to get a bit of a relationship started, according to Samuel. A good way to do that is to bring up a non-trivial “touch point,” he said. This can be a shared alma mater, company, hometown or volunteer experience. Or, it could be a shared interest in the mission of the company.
“By you bringing a touch point up, it tells the person you did some research on them and it can make or break the person deciding to keep the discussion going,” Samuel said. With this sort of connection established, the conversation might continue with them asking more about you and possibly what you could bring to the company.
For Singh, though, the best way to start a conversation is with a cold email.
“It’s all about sending the hiring managers, VPs of data science, CTOs, a really good, specific email about who you are, why you’re interested in the company and a link to a portfolio project or two,” he said.
The goal of the cold email is much the same as a cold call: to build a relationship and get hiring managers or team leads to know about you. By developing a rapport with these people, they might let you know if and when a job application is opening and ask you directly to apply, where it is likely that your resume won’t just be another one in a pile, Samuel said.
Reaching out directly can also help create positions that might not have existed before. Singh said this is especially true of fast-growing companies like maturing startups. Their growth can mean they “can make space for you,” he said.
Samuel described the potential as one where a good conversation with a hiring manager or team lead could result in companies reflecting on their data problems and needs with you and your skill set in mind. “And you know what? You might be the answer to those problems and needs,” he said.
“People [who] can talk about themselves in a broad way have a resume that is not job-specific, but hidden-job-market ready.”
Opportunities are not without their drawbacks, however. The fluidity of roles in data science can also be a problem even when job seekers are relying on publicly posted jobs.
“In our data field, because there are people coming from so many different backgrounds, we’re often going to get screened by more automated systems or get screened by people who might not understand the value that you might be able to bring,” Singh said.
This makes it even more important for data science job seekers to pursue hidden job market opportunities by being proactive about reaching out and starting a conversation, he said. Having a connection with a hiring manager or a team lead can make all the difference.
“There are so many career switchers — people coming from boot camps, people coming from academic backgrounds with Ph.D.s in astrophysics or computational biology — who don’t necessarily have the right skills on paper,” he said. “But if they wrote a good enough cold email that’s like, ‘Hey, I can do the job,’ they can actually get hired.”
And that’s another reason why Singh stressed the value of pursuing stable startups rather than big companies.
“At a big company, if they’re looking for a research scientist, you better have a Ph.D.; if they’re looking for a data analyst, you better be a data analyst,” he said. “But at a smaller company that’s growing fast? They’re going to take a bet on you if you’re smart enough and you reach out and you show enough gumption and you show enough background that you’re actually relevant and motivated and passionate about what they’re working on.”
Regardless of why a job is hidden or where you find it, Samuel said that going after jobs in the hidden job market is ultimately a relationship-driven effort.
“If you chase the job, it’s usually a failing proposition,” he said. On the other hand, good things tend to happen when you chase the relationship instead. But you have to be able and willing to start those conversations.
“People [who] can talk about themselves in a broad way have a resume that is not job-specific, but hidden-job-market ready,” Samuel said.