Senior Data Scientist

Salary: £60,000 - 100,000 per year

Requirements:

• We have 3–5+ years of experience in data science or applied machine learning, preferably in infrastructure, environmental, or urban development sectors.
• We are proficient in Python (pandas, scikit-learn, PyTorch/TensorFlow) and SQL, with experience in geospatial and environmental data analysis.
• We have experience with MLOps tools (MLflow, Docker, CI/CD pipelines) and cloud platforms (Azure preferred) to support scalable and reliable solutions.
• We can influence non-technical stakeholders and communicate complex concepts clearly, especially in the context of infrastructure and environmental projects.
• We have experience mentoring and coaching technical teams, promoting collaboration and innovation.
• We preferably hold a Masters degree in Computer Science, Statistics, Applied Mathematics, or a related field, with a focus on data science applications in infrastructure or environmental domains.
• We are familiar with time-series forecasting, optimisation, and causal inference, particularly in project planning and resource management.
• We have experience with IoT analytics and real-time data processing, including applications in smart cities and connected infrastructure.
• We hold certifications such as Azure AI Fundamentals, Azure Data Fundamentals, or Power BI Data Analyst Associate.

Responsibilities:

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

Technologies:

• AI
• Azure
• CI/CD
• Cloud
• Docker
• IoT
• Support
• Machine Learning
• MLflow
• MLOps
• Power BI
• PyTorch
• Python
• SQL
• TensorFlow
• pandas

More:

We are AECOM, the worlds trusted infrastructure consulting firm, delivering professional services across the project lifecycle from advisory, planning, design and engineering to program and construction management. Our global team of over 50,000 professionals works on transportation, buildings, water, new energy, and environmental projects that help communities thrive. We offer hybrid work options, a dynamic environment, compensation, benefits, and well-being programs, along with opportunities to work on high-impact, transformational projects. We are committed to equity, diversity and inclusion, sustainability, and supporting growth for our people across our global, publicly traded business.

last updated 36 week of 2026