THE PROJECT
The University of Essex in partnership with Colchester Borough Homes offers an exciting opportunity to a graduate with the relevant skills and knowledge to develop a proactive approach to supporting individuals, and particularly children and families experiencing housing insecurity, by identifying and supporting children and households at risk, before homelessness or temporary accommodation disrupts their education, wellbeing and development. This project is funded by Innovate UK.
DUTIES OF THE POST
The duties of the post will include:
• Lead the development of a data-driven framework to identify children, families and households at risk of housing insecurity and homelessness, from data preparation through to testing and evaluation.• Manage, link and analyse housing, local authority and related datasets, ensuring data quality and maintaining clear, reproducible analytical workflows.• Carry out statistical and machine learning analyses to identify factors, patterns and trends associated with housing insecurity, family vulnerability and homelessness risk.• Develop and evaluate risk prediction and decision-support tools that help services identify vulnerable households earlier and support timely intervention.• Work closely with Colchester Borough Homes and other stakeholders to understand service needs, interpret findings, and ensure project outputs are practical and relevant to operational decision-making.• Lead the pilot implementation and evaluation of project outputs, including the analysis of outcomes, collection of stakeholder feedback, and assessment of their usefulness in practice.• Prepare reports, presentations, academic publications and future funding applications, and contribute to the wider dissemination of project findings.• Contribute to the overall management and delivery of the project, ensuring compliance with ethical, data protection and information governance requirements.
These duties are a guide to the work that the post holder will initially be required to undertake. They may be changed from time to time to meet changing circumstances.KEY REQUIREMENTS
• A PhD (or be close to completion of a PhD) in Data Science, Computer Science, Artificial Intelligence, Statistics, Applied Mathematics, Operational Research, or a closely related discipline.• Demonstrable experience of conducting independent research and delivering research outputs.• Strong programming skills in Python for data analysis and machine learning.• Experience working with complex real-world datasets, including data cleaning, preprocessing, feature engineering, and data quality assurance.• Strong knowledge of statistical analysis and exploratory data analysis.• Experience applying machine learning methods, including both supervised and unsupervised approaches.• Experience evaluating predictive models using appropriate validation and performance metrics.• Experience producing reproducible analytical workflows and well-documented code.• Ability to communicate complex technical findings clearly to both technical and non-technical audiences.• Ability to work effectively with external stakeholders and contribute to collaborative projects.• Understanding of data protection, research ethics, and responsible handling of sensitive personal data.• Excellent written and verbal communication skills.
BENEFITS
The post will offer the following benefits:
• The opportunity to participate in professional development courses run by the University of Essex.• An interesting and challenging role, with exposure to a variety of stakeholders.• Full access to university resources to complete the project.• World-leading Academic and Company project supervision, with project support by a dedicated, sector leading Partnerships Office.Please see the attached job pack, which contains a full job description and person specification which outlines the full duties, skills, qualifications and experience needed for this role plus more information relating to the post. We recommend you read this information carefully before making an application. Applications should be made on-line, but if you would like advice or help in making an application, or need information in a different format, please contact resourcing@essex.ac.uk.