Research Associate – Data Scientist

The project will establish robust operational foundations, converting fragmented and early-stage information into reliable, timely insights via user-ready dashboards, prototypes and pilot deployments, to reduce manual effort and error.

Key objectives include building secure data connections and automated refresh, producing a unified data warehouse, developing forecasting and risk-flag tools, and embedding capability through documented procedures, training and a signed handover to business.

Major challenges include fragmented and variable-quality data, the need for clear acceptance criteria and evaluation on real work, and the requirement to introduce new digital practices in a live construction environment.

What will you bring to the role?

• Master’s degree or Doctor of Philosophy in data science, computer science, statistics, artificial intelligence, or a related field or equivalent
• Strong programming in Python and Structured Query Language
• Experience of building and evaluating machine-learning models for structured business data using metrics such as mean absolute error, precision, and recall
• Data engineering experience: design pipelines with scheduled refresh, logging, monitoring, and version control.

The KTP Associate will lead a Knowledge Transfer Partnership (KTP) project that is a collaboration between the University of Kent and Apex Contractors, based in Bexley. The Knowledge Transfer Partnership (KTP) scheme helps businesses to innovate and grow through the aid of discipline specific academic expertise. It does this by linking them with an academic supervisory team and a KTP Associate in a university to work on a specific project.

We seek a graduate with a master’s degree or a doctoral degree to lead a Knowledge Transfer Partnership between the University of Kent and Apex Contractors that will strengthen company data foundations, implement a secure and monitored data layer, and deliver applied analytics and AI solutions to enhance operational performance, planning, quality, and commercial decision-making, with later extension to pricing optimisation.

The project will establish robust operational foundations, converting fragmented and early-stage information into reliable, timely insights via user-ready dashboards, prototypes and pilot deployments, to reduce manual effort and error. Given the current immaturity of our estimating and commercial systems, our primary focus is on operational delivery; the extension into estimating and commercial decision support will follow once the foundational data and systems are stabilised.

Please read all of the documentation attached to the application on University of Kent website.