Senior Data Scientist

AECOM
London
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: mastersSkills: ["Stakeholder communication","Mentoring","Collaboration","Problem-solving","Model lifecycle management"]

Design and deliver predictive and prescriptive AI/ML models that turn complex infrastructure, environmental, and urban-development data into measurable business outcomes. Own AI/ML roadmaps, build models across forecasting, optimization, anomaly detection, and streaming inference, and apply MLOps practices for monitoring and retraining. Collaborate with data engineering to unify batch/streaming/IoT data pipelines, mentor junior data scientists, and communicate results to technical and non-technical stakeholders.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
AECOM
AECOM
3 days ago

Senior Data Scientist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live
Reposted: similar role first listed 6 months ago

Job Summary

Design and deliver predictive and prescriptive AI/ML models that turn complex infrastructure, environmental, and urban-development data into measurable business outcomes. Own AI/ML roadmaps, build models across forecasting, optimization, anomaly detection, and streaming inference, and apply MLOps practices for monitoring and retraining. Collaborate with data engineering to unify batch/streaming/IoT data pipelines, mentor junior data scientists, and communicate results to technical and non-technical stakeholders.
Location: London
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Define and execute AI/ML roadmaps aligned to business objectives, including sustainability and operational efficiency.
  • •Develop and deploy predictive and prescriptive models for demand forecasting, optimization, and anomaly detection in infrastructure projects.
  • •Establish model lifecycle management best practices, including MLOps, monitoring, and retraining to meet global standards.
  • •Extract actionable insights from complex datasets and apply statistical modeling, machine learning, and optimization to solve business problems such as resource allocation and asset lifecycle forecasting.
  • •Collaborate with data engineering to design feature and data-quality pipelines and integrate batch, streaming, and IoT data into unified analytics platforms.

Key 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).
  • •Proven ability to influence non-technical stakeholders and communicate complex concepts clearly in infrastructure and environmental contexts.
  • •Experience mentoring and coaching technical teams, promoting collaboration and innovation.
Experience:3+ yearsInfrastructureEnvironmentalUrban development
Education:Master's in Computer Science, Statistics, Applied Mathematics (or related field)
Skills:Stakeholder communicationMentoringCollaborationProblem-solvingModel lifecycle management
Certifications:Azure AI FundamentalsAzure Data FundamentalsPower BI Data Analyst Associate
Languages:English
Tech Stack:PythonPandasScikit-learnPyTorchTensorFlowSQLGeospatialMLOpsMLflowDockerCI/CDAzurePower BIA/B testingCausal inferenceTime-series forecastingAnomaly detectionIoTStreaming inferenceTelemetry/telematics

Company Brief

AECOM
AECOM is a global infrastructure firm providing design, consulting, construction, and management services across transportation, buildings, water, environment, and energy sectors, delivering large-scale projects for public- and private-sector clients worldwide.
Industry: Civil Engineering
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Los Angeles, United States
Founded: 1990
Glassdoor
Glassdoor: 3.6
WebsiteLinkedInGlassdoor