Research Associate – Data Scientist

Review: Research Associate – Data Scientist (Knowledge Transfer Partnership)

This Knowledge Transfer Partnership (KTP) role presents a compelling opportunity for ambitious graduates looking to make a significant impact within a dynamic construction environment. Partnering the University of Kent with Apex Contractors, this position offers a unique blend of academic rigor and real-world application, designed to propel your career forward.

Advantages for Aspiring Data Scientists:

• Strategic Project Leadership: As a Research Associate, you will spearhead a critical project focused on transforming Apex Contractors' data foundations. This involves not just implementation but also strategic decision-making regarding data infrastructure, security, and AI solutions.
• Cutting-Edge Analytics & AI: You will be at the forefront of developing applied analytics and AI solutions to enhance operational performance, planning, quality, and commercial decision-making. The potential for future extension into pricing optimization highlights the project's evolving and ambitious scope.
• Tangible Impact & Innovation: The project aims to convert fragmented information into actionable insights via user-ready dashboards and pilot deployments, directly reducing manual effort and error. This provides a clear pathway to demonstrate your contributions and see the direct results of your work.
• Exceptional Development Opportunities: Being part of the renowned Knowledge Transfer Partnership programme means access to a generous training and personal development budget. This includes the chance to gain a CMI or similar management qualification, and potential funding support for further academic study (MSc-by-Research or PhD). This is a significant advantage for long-term career growth and specialized knowledge acquisition.
• Industry Exposure & Collaboration: You will gain invaluable experience working within a live construction environment, tackling real-world challenges. The partnership ensures you benefit from the expertise of the University of Kent's academic team, fostering a collaborative and intellectually stimulating work experience.
• Career Advancement: The KTP framework is designed to enhance employability. The structured nature of the project, coupled with the skills and qualifications you will acquire, positions you for significant career advancement upon completion.

Key Considerations for Candidates:

• Academic Foundation: This role requires a strong academic background, specifically a Master’s degree or Doctorate (or equivalent) in Data Science, Computer Science, Statistics, Artificial Intelligence, or a closely related field.
• Technical Proficiency: Essential technical skills include strong programming in Python and Structured Query Language (SQL). Experience in building and evaluating machine learning models using relevant metrics (e.g., mean absolute error, precision, recall) is crucial.
• Data Engineering Expertise: Demonstrable experience in data engineering, including designing and implementing data pipelines with scheduling, logging, monitoring, and version control, is a key requirement.
• Navigating Complex Data Challenges: The project involves working with fragmented and variable-quality data. Candidates should be prepared to address these challenges head-on, establishing clear acceptance criteria and evaluating solutions in a live operational context.
• Adaptability in a Live Environment: Introducing new digital practices within a live construction environment can present unique challenges. A pragmatic and adaptable approach will be essential for success.
• Project Management & Communication: While technical skills are paramount, the ability to embed capability through documented procedures and training, culminating in a formal handover, indicates a need for strong project management and communication skills.

This Research Associate position is an exceptional pathway for individuals seeking to bridge the gap between academic research and industrial application. The comprehensive support structure, combined with the challenging yet rewarding nature of the project, makes this a standout opportunity for those aiming to become leaders in the field of data science and AI.