About the Team:

You’ll be joining a dynamic data innovation team focused on building data models using spatial and geospatial data. The team is at the forefront of driving growth through new, digital-first revenue streams in high-potential areas such as 5G, IoT, Data Analytics, and Artificial Intelligence. We develop cutting-edge solutions that transform mobile network data into actionable insights for the business and its customers.

Role Overview:

As a Data Consultant, you will support the development of scalable, efficient, and production-ready data products and models. You'll work on an impactful initiative to infer user locations more accurately using Mobile Network Data (MND) and help create a proof of concept for a localized population density model.

Key Responsibilities:

• Enhance and refine methods to infer user locations from mobile network data.
• Create, test, and deliver a proof of concept for a new population density product.
• Build scalable, high-performance data-centric solutions using modern tools and techniques.
• Develop and maintain reliable data pipelines to support analytics and model deployment.
• Collaborate closely with data engineers, developers, and product managers in a fast-paced environment

Top 5 Essential Skills:

1. Strong background in data modelling for analytics and insights.
2. Expertise in writing, deploying, and optimizing code in Python, SQL, or similar languages.
3. Proven experience working with geospatial data and understanding of spatial modelling.
4. Proficient with Git for version control and collaboration.
5. Solid understanding of data-centric architecture and best practices.

Desirable Skills:

• Experience working within the Azure cloud environment.
• Familiarity with GIS tools and spatial analysis methods.
• Exposure to CI/CD pipelines for continuous development and deployment.

This is a unique opportunity to shape the future of location-based intelligence within a leading digital business. If you’re a curious and capable data professional with a passion for geospatial insights and scalable modelling—we want to hear from you.