Senior Data Scientist

Overview

In this role you will drive data‑driven decisions across global infrastructure projects, advancing analytics, AI/ML strategies, and IoT insights. You’ll collaborate with cross‑functional teams to embed data science into operational workflows and deliver measurable value. You’ll shape AI/ML roadmaps, develop scalable models, and mentor colleagues, all within a mission to enable sustainable and efficient infrastructure outcomes. This is a chance to apply advanced analytics at scale in a renowned, globally connected firm.

Pay / Benefits

• hybrid work options
• comprehensive benefits and well‑being programs
• global exposure
• diversity and inclusion focus
• equal opportunity employer
• onboarding and development opportunities

Responsibilities

• Define and execute AI/ML roadmaps aligned with business objectives, focusing on sustainability and efficiency
• Develop and deploy predictive and prescriptive models for use cases such as demand forecasting, optimization, and anomaly detection in infrastructure projects
• Establish model lifecycle practices (MLOps, monitoring, retraining) in line with global standards
• Extract insights from complex datasets to inform strategic decisions across infrastructure, environment, and urban development
• Apply statistical modeling, ML, and optimization to high‑impact problems like resource allocation and asset forecasting
• Design experiments (A/B testing, causal inference) to measure impact of data initiatives on project outcomes
• Collaborate with data engineering to build feature pipelines and ensure data quality from diverse sources (geospatial, environmental, operational)
• Support integration of batch, streaming, and IoT data into unified analytics platforms for global projects
• Analyze real‑time sensor and telematics data for predictive maintenance and efficiency of connected assets
• Implement anomaly detection and streaming inference to improve asset performance and reduce downtime
• Mentor junior data scientists and analysts, fostering innovation and analytics excellence
• Promote best practices in data science aligning with quality standards and project delivery
• Present outputs to both technical and non‑technical audiences, translating analytics into clear insights

Key requirements

• 3–5+ years in data science or applied ML, preferably in infrastructure, environmental, or urban development sectors
• Strong Python (pandas, scikit‑learn, PyTorch/TensorFlow) and SQL skills, with geospatial/environmental data experience
• Experience with MLOps tools (MLflow, Docker) and cloud platforms (Azure preferred) for scalable solutions
• Proven ability to influence non‑technical stakeholders and communicate complex concepts in infrastructure and environmental contexts
• Experience mentoring and coaching technical teams to foster collaboration and innovation

• Stakeholder influence
• Mentoring and coaching
• Cross‑functional collaboration
• Python
• pandas
• scikit‑learn

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