Senior Data Scientist

Digital Senior Data Scientist 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. Key Responsibilities - 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. Minimum Requirements - 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/TensorFlow) and SQL, with experience in geospatial and environmental data analysis. - Experience with MLOps tools (MLflow, Docker, CI/CD pipelines) and cloud platforms (Azure preferred), ensuring scalable and reliable solutions. - Proven ability to influence non-technical stakeholders and communicate complex concepts clearly, especially in the context of infrastructure and environmental projects. - Experience mentoring and coaching technical teams, promoting collaboration and innovation. Preferred Qualifications - Master’s degree in Computer Science, Statistics, Applied Mathematics, or related field, with a focus on data science applications in infrastructure or environmental domains. - Familiarity with time-series forecasting, optimisation, and causal inference, particularly in project planning and resource management. - Experience with IoT analytics and real-time data processing, including applications in smart cities and connected infrastructure. - Certifications such as Azure AI Fundamentals, Azure Data Fundamentals, or Power BI Data Analyst Associate.