Data / Machine Learning Fellow (US)

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**

• Leverage deep knowledge of climate and earth systems as well as analytical expertise to provide insights to customers and strengthen core product offerings.
• Disseminate climate-related insights via internally and externally-facing visualizations, published articles, and whitepapers.
• Work with large complex data sets solving non-routine analysis problems.
• 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.
• Have a wide impact on 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 [Apply Now].

---

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.
• Conduct end-to-end ML analysis that includes requirements specification, data gathering and processing, model tuning and 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.
• Minimum availability 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 [Apply Now].

---

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.
• Conduct end-to-end ML analysis that includes requirements specification, data gathering and processing, model tuning and 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.
• Minimum availability 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 [Apply Now].

---

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.