Scientific Computing & Spatial Analytics Engineer

ABOUT THE ROLE

In this role, you'll build scientific computing and spatial analytics solutions for a strategic platform inside Anglo American plc, supporting the exploration, extraction, processing, and marketing of copper, premium iron ore, platinum group metals, and diamonds. You'll turn time-series and geospatial data into tools that guide decisions across mining operations in South America, Africa, Australia, Europe, and North America, working alongside a cross-functional team where technical ownership and innovation drive real business outcomes.

RESPONSIBILITIES

• Design and build data-intensive Python applications that transform raw sensor, geological, and operational data into actionable insights.
• Develop and deploy Dockerized services to package analytical models for consistent use across global mining sites.
• Apply spatial interpolation and geostatistical methods to model resource distributions, ore bodies, and operational risk.
• Collaborate with data scientists, geologists, and platform engineers to integrate machine learning models into production workflows.
• Query, structure, and optimize large operational datasets in SQL to support reliable downstream analytics.
• Build and maintain services on Azure, using Container Apps and Service Bus to support scalable, event-driven data processing.
• Support MLOps practices to monitor, retrain, and version models as new field data becomes available.
• Share findings and technical approaches with stakeholders across regions and functions.

REQUIREMENTS

• Strong hands-on experience with Python and numerical/data analysis libraries such as NumPy, SciPy, Pandas, or Polars.
• Practical experience developing and deploying Dockerized applications.
• Working knowledge of machine learning concepts and related statistical methods.
• Proficiency in SQL for querying and managing large datasets.
• Experience with time-series analysis and spatial interpolation techniques.
• Exposure to C++ or .NET (C#) is a plus.
• Familiarity with Microsoft SQL Server, PostGIS, or geostatistics is an advantage.
• Experience with Azure Cloud services, including Container Apps and Service Bus, is a plus.
• Comfortable working independently and collaborating across distributed, cross-functional teams.