By Lisa Chau
CEO Jeremy Schiff founded RecruitBot to help companies find the right candidates up to five times faster by incorporating outreach and sourcing at scale with analytics. His company developed a hiring platform that transformed the entire recruiting process by harnessing the power of big data, artificial intelligence (AI), and machine learning (ML) to understand hiring preferences.
Many companies struggle with hiring great candidates because they are not messaging the right candidates and/or they are not messaging them correctly. As Schiff explains, “If they are targeting the wrong people, it doesn’t matter if their messaging is compelling. If they don’t use compelling and relevant messaging, the candidates won’t respond. By using ML and AI to provide personalized candidates that match the needs of the position, and by automating outreach in a personalized way with bulk outreach, email validation, and template variables, recruiters can save lots of time engaging with relevant candidates. Also, with an approach that allows recruiters to engage in a personalized but scalable way, it’s important that they are able to capture the patterns of who is a good fit when reviewing candidates, and have reliable analytics to continually compare and improve different email campaign approaches to find the ones that are performing the best.”
Job seekers should also leverage ML and AI to their advantage by using relevant keywords. When browsing through appealing job descriptions, note the skills, credentials, titles, and terms that show up repeatedly. Include these details explicitly in your resume and profiles so AI will recognize that you’re an ideal match for those opportunities.
Even if you’re not actively looking right now, refresh your online career profiles or online resume with keywords that capture your latest achievements, training experiences, and areas of expertise. If you are looking, refresh often; most systems prioritize candidates that have changed their data recently.
“Format your resume in a simple, easy-to-read manner, using a clear, professional font and font size. Fancy graphics, special formatting, and ornate text styles can confuse the sourcing AI systems. If you’re applying for a job, always submit the file type specified in the posting, such as a Word document or PDF,” Schiff advises. “That said, use a bulleted experience section under each role describing highlights of your accomplishments. This is where creativity can shine, and is what a recruiter will use to help advocate for you within the company.”
Even if you’re not actively looking right now, refresh your online career profiles or online resume with keywords that capture your latest achievements, training experiences, and areas of expertise. If you are looking, refresh often; most systems prioritize candidates that have changed their data recently.
For instance, RecruitBot’s ML continually refreshes and personalizes the results for a specific position, at a specific company. In some cases, there are obvious things the platform will focus on such as education or job titles. As it learns more over time, the algorithm may concentrate more on skills, where it can understand why a particular person is a great match for the job, even if they don’t have the right title. Even more deeply, it can understand words associated with nuanced concepts like “service leadership”, “ownership oriented”, or “numbers-driven”. Different companies, and even managers in the same companies care about different attributes about a candidate.
“By having the AI assist in the process of finding and engaging the right people, recruiters can spend more time focused on the human things: making sure they are looking for the rights sorts of people for their roles, sending out engaging and exciting messaging, running effective interviews that get the candidate excited for their roles, etc. Ultimately, they spend more time interacting with other people, which most recruiters love to do!” says Schiff.
“The role of a recruiter will be very different in 5 years than it is today. Before it was about knowing which 8 sites to go to, and how to search them, to go and find the right people to engage with them. As tools like RecruitBot streamline this process, the focus will move to other areas like facilitating better alignment with hiring managers, finding the most compelling messaging to engage candidates, running better interviews, etc.”
Advances in AI have been genuinely astonishing and transformative. Those who embrace these technologies will have huge advantages compared to those who don’t.
RecruitBot leverages both ML and AI to create an all-in-one solution for end-to-end sourcing. Schiff explains, “Most tools only solve part of the problem: finding different / relevant candidates, reaching out to those candidates, storing a history of the people you’ve engaged with in the past, optimizing your process, interacting with your Applicant Tracking System (ATS), and sourcing on LinkedIn. RecruitBot solves all of these problems in a single product – it’s a paradigm shift from the standard “recruiting funnel”, where each batch is recruited basically from scratch, to recruiting flywheel, where continued sourcing for similar roles becomes more effective over time. Machine learning improves relevancy, automated personalized outreach & analytics improves response rates.
RecruitBot’s proprietary machine learning algorithms reverse engineer the candidates you are looking for that are similar to those you’ve reviewed. Targeting these types of candidates is what empowers companies to hire the best people for their roles, and allows recruiters to review 5X fewer candidates to find those that are relevant.”
Previously, Schiff worked at OpenTable as Head of Data Science, and Ness Computing VP of Product and Machine Learning.
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