Nathan Di Pietro

I specialised in communications engineering, contributing to major infrastructure projects such as the Bayswater Station Upgrade and the Morley Ellenbrook Line Project. My responsibilities included:

• Supporting the configuration, commissioning, and integration of communications systems, for an example I was involved in the commissioning of over 200 CCTV cameras, ensuring they met project and client specifications.
• Preparing and updating red line mark-ups for engineering drawings to reflect site changes and as-built conditions.
• Providing construction support during installation and commissioning phases, working closely with site engineers and subcontractors.
• Collaborating within a multidisciplinary team, including civil, electrical, and signalling engineers, to deliver integrated solutions.
• Participating in client communications, including status updates, technical queries, and commissioning coordination.
• Gaining hands-on experience with fibre and copper patching, equipment rack installations, and passenger information systems.

This role developed my technical understanding of communications systems in rail infrastructure, strengthened my collaboration and problem-solving skills, and gave me real-world experience working on high-impact public transport projects.

I worked on a data-driven project focused on improving network coverage estimation using machine learning. My responsibilities included:

• Processed and prepared Pentanet’s coverage data to serve as input for machine learning model development.
• Conducted research on various machine learning models, with a focus on classification techniques.
• Designed and implemented a K-Nearest Neighbours (KNN) model to estimate coverage probability based on geospatial and signal data.
• Integrated the model with Pentanet’s website using Docker containers to ensure scalable deployment.
• Developed an internal web application to visualize and test the model's outputs, enhancing team accessibility to results.
• Participated in daily stand-up meetings as part of an agile team, contributing updates and collaborating with developers and data scientists.

This role gave me practical experience in end-to-end machine learning workflows, from data processing to deployment, while also strengthening my skills in cross-functional teamwork and software integration.

• Collaborated with coworkers to complete nightly stocking tasks efficiently and effectively.
• Unloaded arriving product stock and moved to store display areas.
• Reduced stock damage by carefully handling and transporting merchandise from storage to sales floor.
• Contributed to a safe working environment by adhering to safety regulations during overnight shifts.
• Exhibited strong time management skills by consistently completing tasks within assigned deadlines while maintaining a high level of accuracy and attention to detail.