Founded in 2020 and headquartered in Washington, D.C., Impact Observatory is a mission-driven company that brings AI-powered algorithms and on-demand data to sustainability and environmental risk analysis for governments, industries, and markets. Impact Observatory empowers decision-makers with the timely, actionable, science-based geospatial insights they need to succeed.

What we're looking for...

Impact Observatory’s Machine Learning Science team works closely with Engineering and Product teams to identify and develop products using remotely-sensed data and mathematical and statistical modeling and machine learning approaches – especially deep learning. Our products quantify environmental risk, climate risk, and human impacts on global carbon, biodiversity, and sustainable development. We’ve developed best-in-class, automated Land Use Land Cover (LULC) mapping and change monitoring, in near real time at up to global scale.


We are seeking a smart, energetic, curious, and impact-oriented Machine Learning (ML) Scientist, who will be a key player on our ML/Science team. You’ll have the flexibility to identify and scope projects on our roadmap that fit your interests and skillset, whether it’s analyzing forest characteristics with optical sensors, characterizing human development with SAR data, or revealing cropland patterns with time-series data. Our data science team is highly collaborative when it comes to sharing ideas, solving challenges, and building workflows and tools. Ideal candidates will be comfortable working in a dynamic startup environment.

Duties and Responsibilities

  • Propose and scope projects based on stated product and/or R&D requirements
  • Explore and recommend geospatial datasets and imagery for use in model development
  • Develop ML workflows and algorithms for training and/or improving models
  • Collaborate with Engineering to scale and deploy models
  • Provide clear documentation of all workflows and findings for internal reproducibility
  • Contribute to reports, publications, and communications of ML results for technical audiences and the broader public

Education & Experience

  • Bachelor’s or Master’s degree in relevant field, or equivalent work experience
  • >4 years work experience in relevant field (e.g. data science, geospatial analysis, and/or computer vision)

Required Qualifications

  • Experience building and deploying AI and deep learning models
  • Experience with Tensorflow, PyTorch, or equivalent
  • Expertise in Python
  • Experience with Git, or another version control system
  • Strong written and verbal communication skills
  • Excitement to work collaboratively in a startup, remote team environment

Optional (Bonus) Qualifications

  • Experience with geospatial data, satellite imagery, and/or other remote sensing data & techniques (extra points for SAR experience)
  • Experience with geospatial libraries including GDAL/OGR, rasterio, PyProj, geopandas, and shapely
  • Experience with conservation, environment, or climate change related modeling
  • Experience with risk, carbon, or biodiversity modeling
  • Experience with modeling that integrates satellite imagery with socio-economic data to create insights

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.