It seems like there are more candidates than ever before applying for open data science roles. Unfortunately, many—if not most—of those candidates are simply not qualified. So, how do you screen through all of those data science resumes quickly and effectively? We’ve collected some of our best tips to cut through the noise of an […]
As a recruiter, I know that an applicant tracking system (ATS) is one of the most important tools for success. At Dataspace, we rely on our ATS system, HireHive, on a daily basis. During one of our weekly meetings, we had a discussion about what features we felt were missing in our current system and
We considered a new applicant tracking system—read our ATS reviews of 3 popular options. Read More »
Over the years, our data talent recruiting team here at Dataspace has honed our technique for finding and connecting with the best possible data science candidates to meet our client’s needs. As LinkedIn has grown and evolved as the primary space for online recruiting efforts, we have needed to develop platform-specific outreach strategies that are
LinkedIn Recruiting Tips, Part 2: How to Connect with Candidates on LinkedIn Read More »
In the recruiting world, LinkedIn is perhaps the most commonly used platform to connect with potential candidates and build up a recruiting pipeline. But how do you find the strongest candidates for the role you’re recruiting for? Our team of data science recruiters has developed some LinkedIn-specific best practices that allow us to find promising
LinkedIn Recruiting Tips, Part 1: How to Build a Pipeline of Candidates Read More »
As 2023 draws to a close, we are left to reflect on this past year: the roles we worked on, the candidates we spoke with, and the companies that we recruited for. We also like to tally up the most requested data science skills from our searches this year and share our findings with the
The Top 10 Data Science Skills That Were in Demand in 2023 Read More »
We asked AI to create all the images used in this blog post using the free AI-image generation tools found at Fotor and Freepik. The expansion of large language models—such as ChatGPT, BERT, Bard, and LLaMA—has kick-started the conversation about how these AI tools can be incorporated into business operations across industries. As companies strive
Jobs of the future, now hiring: AI job titles and what they do Read More »
To close out our series on data and analytics roles and why they are important to business, we’re going to explore the position of data engineer. Unlike data analysts, who focus on understanding business data, or data scientists, who leverage data to make business predictions, data engineers have an entirely different focus. In our introductory
Meet the Data Engineer: He builds the systems that support data and analytics Read More »
We’ve been exploring the three major areas of data and analytics roles common to the modern data team. In our last post, we took a deep dive into the different types of data analysts out there—all tasked with describing the current state of a business. Similar to data analysts, data scientists collect and analyze business
Meet the Data Scientist: She can predict your business success with data Read More »
In our post laying out the major analytics roles, data scientist, data engineer, and data analyst, we said that… In the broadest sense, a data analyst takes the data collected by a business and uses it to describe what’s going on. These days, taking care of business means dealing with lots and lots of data.
Meet the Data Analyst: She will help you understand your business data Read More »
Wondering what the heck is going on with hiring these days? Why are there so many data-focused job openings and so few applicants? Why are your best candidates ghosting you? The job of recruiting is really a job of marketing and sales. As the recruiter, you’re working to convince your customer (i.e. a candidate) to
Everything you’re doing to recruit top data talent is wrong Read More »
