Careers
Join our team
Our talented global team are always on the lookout for incredible talent to help us achieve our goals.
Our goal is to build the intelligent climate data solutions of the future. We work with the world’s largest investors, data platforms and consultancies, enabling them to assess the changing face of risk in a rapidly changing world.
Jobs at sust global
Are you excited to work at the forefront of climate tech, AI and the global economy? We’d love to hear from you.
Senior Climate Data Scientist (US)
(Full Time, Remote, US)
This is a fast paced, career building opportunity where you will have a positive impact on the world we live in while working with geospatial climate data and collaborating with the founding team. You will be working closely with our CTO and our data science team. Our science and engineering team is distributed across the US and this role is remote friendly.
Responsibilities
You will leverage your deep knowledge of climate and earth systems as well as analytical expertise to provide insights to customers and strengthen our core product offerings
You will disseminate climate-related insights via internally and external facing visualizations, published articles and whitepapers
You will work with large, complex data sets solving non-routine analysis problems, applying advanced analytical methods as needed
Maintain and rethink existing datasets and pipelines to service an evolving variety of use cases
Enable smart analytics by building robust, reliable, and useful data sets that can power various analytic techniques like spatial regression, super resolution, clustering etc.
You will have a wide impact on our current and upcoming base of customers to help distill complex climate data and frontier climate science into actionable signals
Necessary Qualifications
Experience with climate modeling and working with large spatial datasets on fundamental climate variables
Experience working on analysis, validation and exploration with geospatial data in different formats: netCDF and geojson
Experience developing and deploying machine learning models and running data analysis on geospatial and multispectral earth observation datasets
Experience with python, git, and linux command line. Prior experience with cloud based data analysis tools and workflows
Graduate degree in atmospheric science, meteorology, climate/earth systems science, hydrology, civil/environmental engineering, astrophysics or similar fields; PhD/postdoc with professional work experience highly preferred
Minimum Requirements
2+ years of experience working on cloud-native software products in an industry setting
Available to work remote in a full time capacity
Travel expected a few times a year for team offsites
Authorized to work in the US
Apply for the role by sending a copy of your resume to
Data / Machine Learning Fellow (UK)
(Full Time, Hybrid, UK)
This is a fast paced opportunity working with large scale geospatial datasets with a strong climate impact focus. The Fellow will collaborate with the founding team and be mentored on climate data science by a senior data scientist.
Responsibilities
Work with large, complex geospatial data sets, solving non-routine analysis problems and applying advanced analytical methods as needed. The Fellow will conduct end-to-end ML analysis that includes requirements specification, data gathering and processing, model tuning, validation, and structuring data-driven impact stories and presentations.
Desired Qualifications
Data/ML: Experience working on computer vision, statistical inference, and multivariate analysis. Demonstrable experience in PyTorch or TensorFlow. Experience training ML models on large and noisy datasets is a plus. Experience with geospatial data (climate, weather, remote sensing) is a plus.
Tools: Experience building and training models in Python using cloud native workflows.
Social Good: Strong motivation on using the best data for social good and data driven storytelling. Prior experience writing technical blogs/articles, publishing scientific work.
Learning: Interested in working with a small team of experts building new capabilities in an agile fashion.
Minimum Requirements
Currently pursuing MS/PhD in a quantitative discipline, involving experimental design and data analysis.
At a minimum, available to work part time or full time for 10-16 weeks, ideally for a longer term. This is a remote work position, with the option to hybrid work out of our London offices.
Authorized to work in the UK.
Apply for the role by sending a copy of your resume to
Data / Machine Learning Fellow (US)
(Full Time, Hybrid, US)
This is a fast paced opportunity working with large scale geospatial datasets with a strong climate impact focus. The Fellow will collaborate with the founding team and be mentored on climate data science by a senior data scientist.
Responsibilities
Work with large, complex geospatial data sets, solving non-routine analysis problems and applying advanced analytical methods as needed. The Fellow will conduct end-to-end ML analysis that includes requirements specification, data gathering and processing, model tuning, validation, and structuring data-driven impact stories and presentations.
Desired Qualifications
Data/ML: Experience working on computer vision, statistical inference, and multivariate analysis. Demonstrable experience in PyTorch or TensorFlow. Experience training ML models on large and noisy datasets is a plus. Experience with geospatial data (climate, weather, remote sensing) is a plus.
Tools: Experience building and training models in Python using cloud native workflows.
Social Good: Strong motivation on using the best data for social good and data driven storytelling. Prior experience writing technical blogs/articles, publishing scientific work.
Learning: Interested in working with a small team of experts building new capabilities in an agile fashion.
Minimum Requirements
Currently pursuing MS/PhD in a quantitative discipline, involving experimental design and data analysis.
At a minimum, available to work part time or full time for 10-16 weeks, ideally for a longer term. This is a remote work position, with the option to hybrid work out of our San Francisco offices.
Authorized to work in the US.
Apply for the role by sending a copy of your resume to
Machine Learning Engineer (US)
(Full Time, Hybrid, US)
This is a fast paced career building full time opportunity working with large scale geospatial datasets with a strong impact focus. In this role, you will actively collaborate with the CTO and founding team.
Responsibilities
Work with large, complex data sets. solving non-routine analysis problems, applying advanced analytical methods as needed.
Conduct end-to-end product development that includes managing large scale datasets, gathering product requirement specifications, designing and developing cloud native platform components including data processing, analysis.
Desired Qualifications
Data/ML: Experience working on computer vision, statistical inference, and data analytics on geospatial and multispectral earth observation datasets. Demonstrable experience in PyTorch or TensorFlow. Experience training computer vision models on large and noisy datasets. Knowledge of climate modeling is optional.
Domain: Experience in building and deploying production machine learning models.
Capabilities: Experience working with large geospatial datasets using Python. Familiarity with cloud native analytics tools such as CloudSQL, Cloud AI Platform on Google Cloud
Social Good: Strong motivation on using the best data for social good and data driven storytelling. Prior experience writing technical blogs/articles, publishing engineering developments.
Learning: Interested in working with a small team of experts building new capabilities in an agile fashion.
Minimum Requirements
3-5 years of experience working on data heavy cloud-native software products. At least 2 years of industry experience with shipping ML models in production environments.
Available to work remote full time. Option to hybrid work out of San Francisco office.
Authorized to work in the US.
Apply for the role by sending a copy of your resume to
Machine Learning Engineer (UK)
(Full-time, Hybrid, UK)
This is a fast paced career building full time opportunity working with large scale geospatial datasets with a strong impact focus. In this role, you will actively collaborate with the CTO and founding team.
Responsibilities
Work with large, complex data sets. solving non-routine analysis problems, applying advanced analytical methods as needed.
Conduct end-to-end product development that includes managing large scale datasets, gathering product requirement specifications, designing and developing cloud native platform components including data processing, analysis.
Desired Qualifications
Data/ML: Experience working on computer vision, statistical inference, and data analytics on geospatial and multispectral earth observation datasets. Demonstrable experience in PyTorch or TensorFlow. Experience training computer vision models on large and noisy datasets. Knowledge of climate modeling is optional.
Domain: Experience in building and deploying production machine learning models.
Capabilities: Experience working with large geospatial datasets using Python. Familiarity with cloud native analytics tools such as CloudSQL, Cloud AI Platform on Google Cloud
Social Good: Strong motivation on using the best data for social good and data driven storytelling. Prior experience writing technical blogs/articles, publishing engineering developments.
Learning: Interested in working with a small team of experts building new capabilities in an agile fashion.
Minimum Requirements
3-5 years of experience working on data heavy cloud-native software products. At least 2 years of industry experience with shipping ML models in production environments.
Available to work remote full time. Option to hybrid work out of San Francisco office.
Authorized to work in the US.
Apply for the role by sending a copy of your resume to