Head of Data Science - Geospatial & Digital Twins

Location: Vienna, Austria 

Employment: Full-time 

Your Mission at PropX 

At PropX, we are building the definitive Digital Twin of the built world—a living, breathing model of our cities to solve the most pressing challenges in real estate and urban development. Your mission is to architect the core intelligence of this system, transforming vast streams of geospatial and real-time data into predictive, actionable insights. 

What You'll Build and Own 

● Architect & Develop Predictive Models: You will design and implement sophisticated spatio-temporal models to forecast ESG property value dynamics and simulate the impact of urban development, fusing diverse datasets from BIM and GIS to IoT. 

● Build the Geospatial Data Foundation: You will take ownership of our core geospatial data infrastructure, designing scalable data models in PostGIS and building robust data pipelines to ingest, process, and integrate heterogeneous data sources (vector, raster, point clouds, 3D models). 

● Drive R&D into Novel Methodologies: You will explore and apply cutting-edge techniques in spatial statistics, machine learning, and simulation (e.g., GWR, agent-based modeling, graph networks) to uncover non-obvious relationships within the urban ecosystem. 

● Shape the Technical Roadmap: In close collaboration with our product and engineering leadership, you will contribute to the strategic direction of our data platform, evaluating new technologies and defining best practices for MLOps and technical data governance. 

The Toolkit You'll Bring 

Core Qualifications: 

● 5+ years of hands-on experience in data science, with a strong focus on geospatial data analysis. 

● Expert-level proficiency in Python and its scientific computing ecosystem (GeoPandas, Pandas, Scikit-learn, Rasterio, Shapely). 

● Advanced skills in SQL and deep experience with spatial databases, particularly PostGIS, including performance tuning for complex queries. 

● Proven experience in developing and deploying predictive models in a cloud environment (preferably AWS, AZURE). 

● A strong theoretical foundation in GIS principles (projections, topology) and machine learning concepts. 

Preferred Qualifications: 

● MSc or PhD in Geoinformatics, Computer Science, Urban Analytics, or a related quantitative field. 

● Experience with 3D geospatial data (e.g., Point Clouds, 3D Tiles) and/or AEC data formats (BIM/IFC, CityGML). 

● Familiarity with MLOps tools (e.g., MLflow, SageMaker) and containerization (Docker). 

● Experience with simulation techniques or network analysis (e.g., NetworkX). 

● A track record of contributing to open-source projects or academic publications. 

● Experience with the 3D Unity game engine pipeline is a plus 

Our Tech Ecosystem 

● Backend: Python 

● Data Science & GIS: GeoPandas, Scikit-learn, Rasterio, PostGIS 

● Cloud & DevOps: AWS (S3, EC2, RDS, SageMaker), Docker 

● Collaboration: Git, JIRA 

What PropX Offers You 

● A Mission That Matters: The opportunity to work on one of the most intellectually stimulating challenges in data science in Austria — modelling the complexity of our cities to build a more sustainable future. The opportunity to work on a fully funded project on functional digital twin cities, one of the very first of its kind in Europe. 

● Ownership and Impact: A foundational role where you will shape the core IP of our company and have a direct, tangible impact on our product and strategy. 

● World-Class Environment: A competitive salary, potential for equity participation (VSOP), a generous professional development budget, and flexible working arrangements. 

● Vienna Lifestyle: The chance to live and work in Vienna, consistently ranked as one of the world's most livable cities. 

About PropX 

PropX is a technology company dedicated to creating the definitive Digital Twin of the built world. By fusing data from architecture, engineering, real estate, and the urban environment, we provide decision-makers with the predictive insights they need to build, manage, and invest more effectively.