Human resources are a supportive field present in every company with increasing importance as employees become more and more critical asset. Traditionally HR is less digitalized and data driven applications are still in early adoption stage in most cases, which is both opportunity and disadvantage at the same time. But recently “people analytics” is a very hot topic, and more solutions to be expected to come in the market in the immediate future.
Proposed tech stack: Linux, Python (Anaconda), Scikit-learn, NLTK, gensim, TensorFlow, PyTorch
Job Application assistant for candidates
Chatbot for facilitating application. Engages candidates in personalized career discussions and recommends positions that fit them best, potentially in the form of a chatbot application, optionally with interview scheduling, FAQ.
Recruitment assistant for recruiters
Digital tools for candidate recommendation, predictions without bias about the best suited candidates. Predictions about possible fitting, performance and employee engagement before actual hire. Comparison and evaluation of alternative candidates with respective match scores. Candidate pre-screening with intelligent information extraction from CVs and other written or spoken sources.
Semi-automated or fully automated interview conducting with evaluation of both interviewees and -- in case of semi-automated -- interviewers. Analysis of intelligence, facial expressions, speech patterns, behavioral and other personal traits.
Tracking rejected candidates
Frequent post-checking of rejected applicants’ later statuses -- employment, public careers, professional achievements -- could give feedback about the quality of the decision making about hires.
HR generalist assistant
Chatbot for general questions to handle all internal HR related inquiries from employees.
Also an assistant to accommodate new hires to the everyday life of the company with possibly personalized learning program, initiatives, getting around office and its environment, following progress, make practical recommendations.
Company real-time insights
Collecting up-to-date information about the company and its products, services from the market and employee sentiments, possibly in the form of ratings by social listening.
Career path alignment with goals defined by employee and team manager; position recommendation based on existing skills and matching opportunities; skill management (gaps, recommendations), defining motivation, engagement, identification of potential mentors or peer groups.
Collective information system about past projects and achievements with general access by staff. What is our knowledge and experience about any upcoming task? Who is most competent? What similar solutions do we already have?
Prediction of employees’ receptiveness to leave company, especially in case of key staff with emotion and activity check.