The Best Data Scientist Job Sites

Rejection As Far As The Eye Can See

Rejection is hard. Spending hours scrolling through hundreds of job posts on job boards just to submit my resume into an abyss I rarely heard back from prepared me quite well for the online dating world. If you want to maximize your chances on job boards use our free data science resume templates and guide for 2022.

Now that I get to spend some of my time writing articles on topics I find interesting I wanted to look under the hood and see what the deal was with job boards. I took a snapshot of data science jobs posted on Glassdoor, LinkedIn, and Indeed and came up with the answers to some of my questions (my methodology for getting the data is detailed below):

• 10% of companies post 66% of the jobs across Glassdoor, LinkedIn, and Indeed.
• Recruiting agencies account for 14% of all the job posts on the three sites. Nothing screams “Apply here!” like when a job description won’t even tell you which company you’re applying to.
• If you’re going to use a job board I recommend Glassdoor. Glassdoor has a similar number of data science jobs as LinkedIn but the % of jobs that are posted by recruiting companies is much lower (8% vs 23%, respectively). 
• If you want a more curated experience use BeamJobs. We’ll send you 5 job recommendations each month that match exactly what you’re looking for. We have the highest coverage of companies (70% of companies in our system are not on any other job board) and we exclude all recruiting companies. 

Which Data Science Job Board Should You Use?

The interactive chart above was created to help you understand which job board(s) you should use if you’re actively applying for a new data science job in any of the cities listed. 

You want the most bang for your buck when you’re choosing which job board to use (if any at all). You want to start with the site that has the greatest coverage of different companies and job posts that are not from recruiting agencies. I chose the metrics in the chart above to help you decide where you should go if you want to use one of the big three job boards:

• Distinct Non-Recruiting Firms: This is the total number of distinct companies on a job board that are not recruiting firms and are not on any other job board. To get the highest ROI from job boards you want to apply broadly and you want to start with the site that has the most unique companies. Focusing on companies that aren’t on other job boards has the big benefit of reducing the number of applicants you’re competing against. If a job is on all three sites it’s a safe bet it will generate more applicants than a job that’s only on one of the sites.
• Non-Recruiting Firm Jobs: This one is all in the name. It’s the total number of data science job posts on a given site that are not from recruiting firms.

Power Posters Pursue Pareto Principle (or, 20% of companies post 76% of jobs)

The alliterative title for this section took me WAY too long to come up with. Like I stated above, 10% of companies posted 66% of data science job openings and 20% of companies posted 76% of the jobs across Indeed, Glassdoor, and LinkedIn. This roughly follows the Pareto Principle. I’m always surprised how frequently the 80/20 rule bears out in real life.

Now it’s time to play a game. Which non-recruiting companies posted the most data science jobs on these job boards? (Cue Jeopardy music):

• Up first, the company behind the supercomputer that demolished Ken Jennings and Brad Rutter in Jeopardy! (I promise this is my last Jeopardy reference, I'm just really excited for the "Greatest of All Time" showdown). IBM accounted for 2.2% of the total job posts.
• In a close second we have Amazon at 2.0% of the total data science posts.
• Uber and Novartis are tied for third with 1.4% of the total job posts.

All of these companies paled in comparison to the total number of jobs posted by the recruiting agency Harnham. They accounted for a whopping 3.1% of all data science job posts on Indeed, Glassdoor, and LinkedIn.

As a side note, I wanted to mention how good Amazon is at SEO. If you Google “Data Science Jobs” Amazon is the only company not in the hiring space to rank on the first page. They link to a page where they show they’re hiring for 250 data scientist positions! This keyword gets roughly 12,000 searches in the US each month so they likely get a sizable number of applicants with this approach.

Recruiting Agencies Account for 14% of All Job Posts

Not all sites are created equal in this regard. 23% of data science job posts on LinkedIn were from recruiting agencies, while for Glassdoor and Indeed 8% of all posts were from recruiting agencies. Keep in mind these are conservative estimates. I manually tagged companies as recruiting agencies so I likely overlooked some.

While 23% of the data science job posts on LinkedIn were from recruiting agencies, the agency posts are largely concentrated in the later pages of results. For example, here is the breakdown of the % of jobs from recruiting agencies by page number for Linkedin in Boston:

Remote Data Science Jobs

It is slim pickings for remote data science roles on LinkedIn, Glassdoor, and Indeed. I’m not sure if this is because full-time remote data science roles are just uncommon or if for some reason companies aren’t paying to sponsor these jobs on the job boards. Here are the total number of remote roles in the US for each of the job boards and for BeamJobs from non-recruiting companies:

• Indeed: 9
• LinkedIn: 11
• Glassdoor: 16
• BeamJobs: 54

You can see that our remote totals are higher than the job boards but still there aren’t as many roles as even the smallest city we collected data for. At BeamJobs we index jobs directly from company websites (it’s not pay to play) so it might just be the case that these jobs are few and far between. With that said, we’re still in the early days of our product so our remote coverage will only improve over time.

The Best Way to Find Data Science Jobs

One of the most important lessons I learned from being a data analyst before starting BeamJobs is that data without concrete recommendations is not really that useful. Get the data, play around with it, and draw actionable conclusions from the analysis. With that said, if I were to recommend a job board for a data scientist to use I would recommend Glassdoor. I think the user interface is really pleasant, they have the lowest percentage of recruiting companies on the site, and their job coverage is solid. While all three job boards have quality issues in terms of some really bad job descriptions, anecdotally the quality on Glassdoor seems higher.

If you’re interested in a more curated job search experience use BeamJobs. We index thousands of data science and engineering jobs then handpick the five each month that best fit what you’re looking for. Since there is a human on the other end we won’t send recruiting agency jobs and we only send roles with compelling job descriptions.

Data and Methodology

The data I’m presenting here is a snapshot in time from November 17, 2019. That is, I looked at all of the data science jobs on Glassdoor, LinkedIn, and Indeed on that day in the cities listed in the chart above. How did I get this data? The good old fashioned way, manually. I’ve made a lot of mistakes since I started BeamJobs, one of which was engineering too early. So rather than build a scraper for this one-off analysis I spent about 15 hours getting all of the companies hiring for data science roles.

To execute my searches I filtered the jobs to contain the exact string “data scientist”, were full-time, and were within 10 miles of the city I was searching for. For remote roles I chose the location as “remote” based in the US. I did some minor processing of company names to standardize them across sites (for example removed the “Inc” from company names).

Once I had all of the companies hiring data scientists I looked up each company to see whether or not it was a recruiting agency. For the purposes of this analysis I counted any company that was not directly hiring as a recruiting agency. Interestingly enough, there is some crossover in terms of job boards advertising on other job boards:

I then looked at the non-recruiting companies on each site to see which companies no other site had. The logic here is that if you’re going to use two job boards you want to be sure you’re not seeing the same roles and companies on each job board. So by starting with the job board that has the highest coverage (in terms of total number of roles and total number of unique companies) you can save yourself time and effort.