About Us

 

Climate X is a purpose-driven climate adaptation data company set to revolutionise how the world manages assets, property, and infrastructure. 

We apply cutting-edge, peer-reviewed science to help prevent the worst impacts of climate change. We combine climate projections, remote sensing observations, and modelling to project the frequency and severity of physical climate risks such as floods, subsidence, storms, etc.

Our SaaS platform lets financial institutions and real estate firms look at future climate pathways to:

  • help identify how property/company assets could be damaged by severe weather events and
  • what that damage might do to the asset valuations.
  • become more resilient to climate change and make smarter investment and lending decisions.

We advocate diversity with our founders, team, and investors from various backgrounds.
We’re not building just a team but a place of innovation where problem solving, and fun coexist to address the most significant challenge our society is facing now. 

 

The impact you’ll own

As Senior Scientific Software Engineer, you will develop hazard model code with our expert science team, and working to meet the scientific challenges we face when modelling the impacts of climate change on a global scale. You will be instrumental in developing, maintaining, and optimizing novel code, libraries, and packages to derive new insights into the impact of climate change.

 

You will contribute to software engineering and pipeline design for our climate and hazard model workflows, helping to improve their implementation to improve efficiency, robustness and scalability on high performance clusters.

 

 

You will lead longer-term projects focused on improving our code base, ensuring its efficiency, scalability on the cluster, and overall robustness.

 

This position offers an exciting opportunity to make a meaningful impact in addressing climate change challenges while working with cutting-edge technology in a dynamic and collaborative environment.

 

 

 

 

Essential Skills

 

  • Proven experience and strong programming skills in Python, including numerical libraries such as numpy, (geo)pandas and xarray.
  • Proven ability to write robust, scalable code for handling big data challenges, and experience refactoring, optimising, and parallelising existing code.
  • A PhD or equivalent experience in an area related to computer science, climate science, Earth observation, remote sensing, (astro)physics, applied stats, or computational methods for physical sciences.
  • Experience with geospatial data (raster and vector) and related tools such as gdal.
  • Excellent communication skills with the ability to explain complex concepts to non-technical audiences, and bridge between the technology and science teams.

 

Desirable Skills

 

  • Ability to understand scientific concepts around climate and hazard modelling and the physical processes involved. Ideally a higher education qualification in a relevant physical science or engineering.
  • Knowledge of best practices in software engineering, and expertise with git version control.
  • Experience with object-oriented Python programming.
  • Experience developing and deploying custom libraries and implementing tests.
  • Expertise with AWS or similar cloud platforms such as Microsoft Azure, Google Cloud
  • Experience with NVIDIA’s CUDA API
  • Experience working with hydrodynamical models in an HPC environment.
  • Experience with parallel computing tools such as Dask, MPI, OpenMP
  • Machine learning expertise, with tools such as scikit-learn.
  • Hands-on, can-do attitude, great interpersonal skills, and ability to collaborate effectively.

 

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