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Research Associate

In or around this area


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up to £50000 per annum

Job Description

Research Associate

We are seeking a PhD graduate (or close to completion) who will be responsible for the development and integration of machine learning models which match candidates to roles with HR GO's clients; leveraging the millions of datapoints collected by HR GO to embed within HR GO's systems ethical and transparent scoring, so that candidates can understand their progress towards and likelihood of achieving their next job.

The KTP will mainly focus on developing a Machine Learning model which will power the job matching and recommendation engine within HR GO's 'Candidate Account' web application. The model will be designed and implemented so that it can be used by multiple areas of the HR GO business.

This is a unique opportunity to work at HR GO and to engage with significant technical and commercial challenges. HR GO operates in the Staffing Industry and their revenue generating activities are the placing of candidates into temporary or permanent employment. In addition to placing candidates, HR GO provides both candidates and clients with online platforms to support their work. These may include facilities to manage timesheets, management information, onboarding, checking billing information, and ordering.

Key Accountabilities / Primary Responsibilities

  • To score candidates' suitability for jobs using HR GO data.

  • To make job recommendations to candidates based on their suitability.

  • To accelerate and enrich the feedback loop between candidates and employers.

  • To deliver a transparent 'clear box' method of scoring, recommendations and matching to be shared and iterated with candidates and employers.

  • To incorporate relevant contextual time series data collected by HR GO, for example, on attendance, shift duration, tenure, earnings, sickness, holiday etc. to further train models.

  • To ensure that the rich data collected by HR GO is used ethically, responsibly and in compliance with the rights of the data subjects (GDPR and otherwise).

  • Reporting on each phase of testing to stakeholders and scientific communities.

  • Writing of scientific papers associated with the work for publication in peer reviewed scientific journals.

  • Training HR GO's team members on the new systems and models developed during the project.

Interested? Apply online today

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