Jobvite, a San Francisco-based recruiting software firm, has launched a data science strategy that provides recruiters and candidates with improved experiences.
SAN MATEO, January 7, 2020 — Jobvite, a San Francisco-based talent acquisition software company, has launched an innovative data science strategy to power its suite of HR products. This initiative focuses on ensuring recruiters are served the best-fit candidates and eliminating wasted time for both recruiters and candidates. This strategy incorporates multiple algorithms and sources of data that span company-wide preferences for hiring as well as the individual recruiter-level preferences. The solutions are designed to work across all positions, recruiter preferences, and industries and will be integrated within the product starting in early 2020.
Talent acquisition teams are faced with unprecedented hiring challenges. Unemployment has been hovering at record lows, falling as low as 3.5% in October 2019. 67% of recruiters say they lack skilled and high-quality candidates to meet the needs of their business, according to Jobvite’s Recruiter Nation Survey. And 52% of recruiters say that competition for skilled talent is intense, from that same survey. These challenges are driving the need for improved speed and quality of talent acquisition.
In addition to the critical recruiter-focused application, the new algorithms will also help candidates get the best potential jobs served to them based on their previous experience, interests, and application history. For candidates, this increases their ability to discover and apply for roles that they may not have initially considered.
“With the technology and platforms that exist to make quick applications possible for candidates, recruiters are sorting through mountains of resumes —many of which are not great fits for the role,” said Zach Linder, Vice President, Analytics and Machine Learning at Jobvite. “By taking the sorting tasks off their shoulders, recruiters can find and hire well-matched candidates faster.”
Jobvite pioneered the project in early 2019 alongside their data science agency, Predictive Partner, and plans to continue to enhance and build out additional algorithms to support the goal of improved candidate matching throughout 2020. In addition to this project, Jobvite also works with Predictive Partner on other initiatives, including response optimization and engagement scoring.
“Jobvite’s objective to build a data-first company has allowed our data science team to quickly develop algorithms that reflect the unique and changing preferences of a recruiter,” said Morgan Llewellyn, CEO of Predictive Partner. Morgan continued, “Our goal is to create a solution that eases the pressures of monotonous daily tasks so the recruiters can focus on what they do well—finding the perfect candidates.”
Jobvite is leading the next wave of talent acquisition innovation with a candidate-centric recruiting model that helps companies engage candidates with meaningful experiences at the right time, in the right way, from first look to first day. The expanded Jobvite platform infuses automation and intelligence into today’s expanded recruiting cycle to increase the speed, quality and cost-effectiveness of talent acquisition. Focused exclusively on recruiting software since 2006 and headquartered in Silicon Valley, Jobvite serves thousands of customers including Ingram Micro, Schneider Electric, Premise Health, Zappos.com, and Blizzard Entertainment. Jobvite continues to empower companies to provide an even richer hiring experience with its recent acquisitions of Talemetry, RolePoint and Canvas – enabling hiring teams to source, engage, hire, onboard, and retain top talent with one end-to-end platform. To learn more, visit www.jobvite.com or follow the company on social media @Jobvite.
About Predictive Partner
Predictive Partner is a leading data science firm that solves critical business problems. Leveraging predictive analytics, data science, machine learning, and artificial intelligence, Predictive Partner achieves transformational business results for its clients. A team-based model with experienced Ph.D. data scientists allows clients to deploy and scale their data strategies with low risk and high dependability.