Our mission

Climate change is causing deep uncertainty at all levels of society, with climate volatility reducing the security of all land-based assets and posing a multi-level security threat for the functioning of enterprises, societies, and governments.

Mitiga is a spinoff of the Barcelona Supercomputing Center, which hosts MareNostrum, one of the most powerful supercomputers in Europe.

Mitiga's mission is firmly rooted in employing cutting-edge science and technology to mitigate the multifaceted risks posed by climate-driven perils. Our approach spans a spectrum of temporal scales, from real-time and annual forecasts to projections spanning the next century. This comprehensive perspective on risk, coupled with our capacity to transfer risks to capital markets via catastrophe bonds, positions us to significantly contribute to enhanced climate mitigation, resilience, and equity.

And we need you.

The role

EarthScan is seeking a talented Data Scientist with a geospatial statistics background to play a key role in shaping the future of our EarthScan Ratings product. You will be instrumental in developing innovative methods to quantify climate risk exposure and impact across various hazards. Your work will be highly impactful, informing a wide range of use cases served by EarthScan, and directly contributing to the creation of next-generation risk rating products.

Who you are

• Super confident in geospatial statistical methods, including spatial autocorrelation, point pattern analysis, and geostatistics.
• Adept at building and managing ETL pipelines for data transformation and integration.
• Possess proven experience working with spatial climate data and climate modelling outputs.
• A Python pro with proficiency in geospatial libraries like GeoPandas.
• Skilled in using GIS software for data visualization and insightful analysis.
• A gifted communicator with the ability to effectively present complex findings to both technical and non-technical audiences.
• A meticulous problem-solver with a strong analytical mind.

Bonus Points:

• Experience applying machine learning techniques to analyze climate data.
• A solid understanding of climate modelling principles and methodologies.
• Familiarity with risk modelling concepts and practices.

Your Impact

• Design a robust methodology to transform raw climate risk metrics (e.g., flood depth, wind speed) into standardized, comparable risk rating scores. This will allow for apples-to-apples comparison of diverse climate hazards. The methodology should be scalable to accommodate the integration of new data sources.
• Develop a system to generate a single, unified risk rating score that effectively captures the combined impact of multiple climate hazards on a specific location or asset.
• Craft rating methodologies that intelligently leverage real-world damage and loss data to generate more meaningful and actionable risk assessments.
• Collaborate with the team to build efficient, scalable pipelines for generating risk ratings for large datasets, ultimately streamlining their integration into crucial decision-making processes.