About Us
We are a leading global climate risk and analytics provider located in London, UK, and New York, US. Earlier this year, we closed Series A funding led by GV (Google Ventures) and are on a fast trajectory to lead the financial services and asset management industries with our B2E SaaS platform, comprising three products: Carta, Spectra, and Adapt, which address customer climate risk challenges across their workflows.
We are at a pivotal point in scaling our product offerings, expanding our market reach, and refining our strategy to sustain continued success.
About the role
We are seeking a Scientist with extensive experience in geospatial data engineering and model development (physical, statistical, or machine learning), with expertise in Earth Observation processing techniques and sources. The ideal candidate will be adaptable to tackle technical challenges across geospatial and physical modelling domains. As a key member of the Science Team, you will play a crucial role in building scalable geospatial tools, supporting hazard scientists in complex modelling tasks, creating high-quality input datasets, and future-proofing our processes to scale to new geographies and methodologies.
The impact you\’ll own
- Solve geospatial engineering challenges: Optimize workflows for massive global geospatial datasets, from processing terabytes of satellite imagery to scaling river flood models on a continental scale. Ensure models are robust, high-performance, and scalable.
- Champion best practices: Shape geospatial science workflows by creating efficient, reusable tools for model validation and systems that ensure reproducibility. Lead efforts to make geospatial work seamless, enabling the team to focus on complex challenges.
- Build new geospatial datasets: Transform diverse raw datasets into standardized, analysis-ready, cloud-optimized formats, such as compiling wildfire observations or harmonizing tropical cyclone data for hazard modelling.
- Geospatial leadership: Collaborate with hazard scientists to enhance the complexity, precision, and scope of their models, enabling accurate, data-driven hazard insights across various environments.
Essential Skills
- Experience working with large geospatial raster and vector datasets, including Earth Observation or climate data.
- Proficiency with processing large, complex datasets using Python-based geospatial tools (xarray, numpy, scipy, dask, geopandas, OGR, GDAL).
- Strong quantitative skills with the ability to extract insights from spatial data.
- Familiarity with modelling concepts from hydrology, atmospheric sciences, or environmental sciences.
Desirable Skills
- Experience with cloud platforms (AWS, GCP, Azure) for geospatial data storage and distributed processing.
- Experience processing optical or radar Earth Observation datasets.
- Experience in geospatial machine learning or physical/semi-empirical modelling.
Qualifications
- PhD or equivalent in Earth Observation, geospatial data engineering, or environmental sciences.
- At least 3 years of industry experience in the geospatial domain.
Benefits
- Contribute to impactful work addressing climate change.
- Annual training and conference budget (£1,000).
- Biannual appraisals and monthly pay reviews.
- Pension scheme, flexible hours, and hybrid working.
- Wellbeing support, generous holiday allowance, social events, and office amenities.
- Additional benefits include cycle-to-work scheme, enhanced parental leave, pawternity leave, and dog-friendly office.
Equal Opportunities
Climate X values diversity and is an equal opportunity employer. We do not discriminate based on race, religion, gender, or other protected characteristics. We are committed to an inclusive environment and welcome applicants from all backgrounds.
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Contact Detail:
Climate X Recruiting Team