2024 Data Scientist Work Placement

Job Description

Dedicated to sustainable development, Arup is a collective of advisors and experts working across 140 countries. Founded to be both humane and excellent, we collaborate with our clients and partners using imagination, technology, and rigour to shape a better world. We put sustainability at the heart of our projects and strive to build a more sustainable, resilient, and equitable future.

With a love of innovation from design to project management, we are the trusted consultants that make the extraordinary possible. That is why, at Arup, the possibilities are infinite.

Arup Ireland

Established in Ireland in 1946, we have over 650 staff across our Dublin, Cork, Limerick and Galway offices.

The Opportunity

We're looking for a Data Scientist intern to join our Data Insights team. You will have the chance to work across a unique & wide-ranging portfolio of data science projects. The role is focused on delivering data driven solutions to both internal and external clients.

Your responsibilities:

• Based in a team of data scientists/analysts, the role is focused on delivering data driven solutions to real world problem in the built environment.

• Arup are represented in a very wide range of sectors within the build environment sector including buildings, transport, sustainability, energy and water related industries and we seek to exploit opportunities to deploy industry leading data science to these and other areas. Our drive to build a more sustainable, resilient and equitable future is central to all our projects.

We seek the following qualifications, attributes and skills:

• Studying computer science, computer engineering or equivalent.

• Proficient in the use of programming languages to perform data analytics, including Python and SQL.

• Has experience in the analysis of data using Tableau, Power BI and/or AWS QuickSight in the development of dashboards.

• Has a good understanding of basic machine learning algorithms.

• Experience in preparation of data, cleaning and transforming it for downstream data analysis tasks.

• Ability to “think outside the box” in creatively solving problems

• Have a passion for learning new technologies.

Some of our team’s exciting projects:

Predicting Bike Share Usage: Accurate predictions of usage allow operators to rebalance public bike share schemes much more efficiently. The data insight team applied machine learning techniques to public bike share data from the Coca-Cola Zero Bikes scheme in Cork. The model developed blends various historical datasets, such as trips taken, weather conditions, college terms and holidays to produce accurate usage predictions which can allow the operator to manage the scheme more efficiently.

Northern Ireland Water is a government owned company that provides water and sewerage and is Northern Ireland’s largest electricity consumer. NI Water have extensive monitoring on their water treatment works, however, the data was not gathered in a central location where it could be analysed to inform longer term operational and strategic decision making. In collaboration with Arup’s water domain experts, the data insights team utilised this data to identify opportunities to improve energy efficiency. These insights have allowed NI Water to reduce the energy usage at their water treatment works, improving their sustainability and reducing costs.

M50 eFlow Data Insights Lab: Arup manage the operator of the M50 eFlow tolling on behalf of Transport Infrastructure Ireland. Arup have established a Data Lab on this project with the aim of embeding the use of data insights into all aspects of eFlow's activities. The Data Lab is delivering use cases such as advanced analytics, anomaly detection and operational dashboarding solutions to TII using the operator’s data lake, which contains vast quantities of transaction level data.

Prediction of Post-Accident Road Network Recovery Time: This project was funded the UK Department for Transport. It addressed the question of “How long will it take for traffic to return to normal conditions after an accident has occurred?”. It applied machine learning techniques to historical traffic and incident data from the M25 in London to develop an incident duration prediction model.

Application Details

• We encourage you to apply early.
• Complete your online application form and an account will be created for you.
• Upload a cover letter, CV, current academic transcript and a sample of your work.
• After the application deadline, we will let you know if you are successfully through to the interview stage.
• Interested candidates must hold a relevant work permission to apply for work placement roles.

• Please note this role is suitable for those who are in full time education and are looking for a placement for the summer months or for those who are required to complete a placement as part of their course requirements.

If you have recently graduated, please apply to one of our '2024 Graduate Programme' roles.