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    Improve HR workflows, employee trainings and hiring processes

    Human Resources

    Human resources is one of the quintessential parts of any company as it is directly affiliated with the lives of employees. Since 2020, HR professionals have faced a radically different landscape: hybrid workforce, virtual recruitment and a heightened focus on diversity and inclusion have introduced new dynamics and intensified existing ones. Increasingly, we need new platforms and technologies to stay ahead, and AI is at the forefront.
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    BlueRectangle
    Use Cases
    How we can leverage ML in Human Resources industry
    Resumé screening
    Candidate matching
    Attrition pattern detection
    Workforce forecasting
    Feedback analysis
    Candidate Recommendation System
    About the client
    Experfy is a platform for freelance jobs. As a startup, it was incubated in the Harvard Innovation Lab and is Deloitte’s main partner for AI projects.
    Challenge
    Matching jobs with the ideal candidates is a top priority and the core of its business.
    Recruiters typically search through dozens or potentially hundreds of profiles in order to find a suitable candidate for a position. Our goal is to reduce the time spent on this manual task, automatically recommending the best profiles for a particular job.
    Results
    Using natural language processing, we identify the candidates with the most relevant skills for a particular job. State of the art techniques like Google BERT were benchmarked to build the recommender system.
    30
    %
    Reduction in cost-per-hire
    Impact
    Thanks to the implemented recommender system, it is possible to recommend only the suitable candidates for a position. It increases the probability of finding a good match between the available open positions and qualified available workers in a timely manner.
    The solution significantly reduces the time spent by recruiters searching through candidate profiles. Overall, stats show that recruiters that use AI see a 30% reduction in cost-per-hire.
    Impact
    Thanks to the implemented recommender system, it is possible to recommend only the suitable candidates for a position. It increases the probability of finding a good match between the available open positions and qualified available workers in a timely manner.
    The solution significantly reduces the time spent by recruiters searching through candidate profiles. Overall, stats show that recruiters that use AI see a 30% reduction in cost-per-hire.
    30
    %
    Reduction in cost-per-hire
    Technologies
    Python, Tensorflow, Docker, Golang, AWS, Transformers.
    Transformers
    AI-based Mock Interview Tool
    About the client
    Our client was a US-based technology company providing professionals with tools to help them leverage their experience and potential. Tools included mock interviews with AI feedback, live interview coaching, and job tracking.
    Challenge
    They approached us looking to understand the current situation of the platform in terms of AI and learn how they could introduce improvements as well as new AI models.
    Results
    Focusing on its mock interview tool, we first looked to diagnose and understand, not only the AI architecture and components already built within the product, but also the problem that it solved and the market it served.
    We focused on three main features which were of special importance to the client: skills detection, body language detection and audit of automatically generated GPT-3 questions. We did initial research on each of these features, to propose alternatives, understand the state of the art in each case, and to make recommendations on the potential implementation of these machine learning projects.
    75
    %
    Save up in cost per screen
    35
    %
    Reduce in turnover
    Impact
    Companies that use interviewing automation tools can make the recruitment process up to 90% faster while also improving the quality of candidates based on past hires.
    More generally, using AI-powered recruiting tools can save companies up to 75% in cost per screen and reduce turnover by 35%.
    Impact
    Companies that use interviewing automation tools can make the recruitment process up to 90% faster while also improving the quality of candidates based on past hires.
    More generally, using AI-powered recruiting tools can save companies up to 75% in cost per screen and reduce turnover by 35%.
    75
    %
    Save up in cost per screen
    35
    %
    Reduce in turnover
    Shape of the picture
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    Let's discover how we can help you
    Training, developing and delivering machine learning models into production
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