Senior Data Scientist

Company Description

Work with Us. Change the World.

At AECOM, we're delivering a better world. Whether improving your commute, keeping the lights on, providing access to clean water, or transforming skylines, our work helps people and communities thrive. We are the world's trusted infrastructure consulting firm, partnering with clients to solve the world’s most complex challenges and build legacies for future generations.

There has never been a better time to be h accelerating infrastructure investment worldwide, our services are in great demand. We invite you to bring your bold ideas and big dreams and become part of a global team of over 50,000 planners, designers, engineers, scientists, digital innovators, program and construction managers and other professionals delivering projects that create a positive and tangible impact around the world.

We're one global team driven by our common purpose to deliver a better world. Join us.

AECOM is seeking a Senior Data Scientist to join our Data Science & Analytics team, contributing to transformative data-driven decision-making across global projects. As part of AECOM’s commitment to delivering sustainable and innovative solutions, the Senior Data Scientist will play a critical role in advancing analytics, AI/ML strategies, and IoT-driven insights to unlock measurable business value across infrastructure, environmental, and urban development sectors.

Reporting to the Data Intelligence Lead, this role will focus on designing and implementing predictive and prescriptive models, driving AI/ML strategies, and collaborating with cross-functional teams to integrate data science solutions into AECOM’s operational workflows. The ideal candidate will bring expertise in advanced analytics, machine learning, and IoT technologies, with a passion for solving complex challenges in the built environment.

• Define and execute AI/ML roadmaps aligned with AECOM’s business objectives, including sustainability and operational efficiency.
• Develop and deploy predictive and prescriptive models for key use cases such as demand forecasting, optimisation, and anomaly detection in infrastructure projects.
• Establish best practices for model lifecycle management, including MLOps, monitoring, and retraining, ensuring alignment with AECOM’s global standards.
• Extract actionable insights from complex datasets to inform strategic decisions across infrastructure, environmental, and urban development domains.
• Apply statistical modelling, machine learning, and optimisation techniques to solve high-impact business problems, including resource allocation, project risk management, and asset lifecycle forecasting.
• Design and run experiments (e.g., A/B testing, causal inference) to measure the impact of data-driven initiatives on project outcomes.
• Collaborate with data engineering teams to design feature pipelines and ensure data quality across diverse sources, including geospatial, environmental, and operational data.
• Support integration of diverse data sources (batch, streaming, IoT) into unified analytics platforms tailored to AECOM’s global projects.
• Analyse real-time sensor and telematics data to enable predictive maintenance and operational efficiency for connected assets in infrastructure projects.
• Implement anomaly detection and streaming inference solutions to improve asset performance and reduce downtime.
• Mentor junior data scientists and analysts, fostering a culture of innovation and excellence in analytics and modelling.
• Promote best practices in data science and analytics, ensuring alignment with AECOM’s quality standards and project delivery frameworks.
• Present work outputs to both technical and non-technical audiences, translating complex analytics and AI/ML concepts into clear, layman’s terms.

• 3–5+ years of experience in data science or applied machine learning, preferably in infrastructure, environmental, or urban development sectors.
• Strong proficiency in Python (pandas, scikit-learn, PyTorch/Tensor Flow) and SQL, with experience in geospatial and environmental data analysis.
• Experience with MLOps tools (MLflow, Docker,…