Emissions Scientist

Emissions Scientist 

Location: MTL or CGY (Hybrid 2x in office preferred, though remote work may be considered)

GHGSat is mapping and tracking the world's greenhouse gas (GHG) emitters. To accomplish this goal GHGSat operates its own satellite and aircraft sensors to collect emissions data, and uses these with third-party data to: 

• Identify and classify potential GHG emission sites 

• Detect, quantify and attribute GHG emissions to sources 

• Generate measurement-informed emissions inventories and other valuable insights from this dataset to our customers. 

The successful candidate will collaborate with other members of the Science and Analytics teams to develop methods to estimate site, sector, and region-level emission magnitudes and behaviour (e.g. persistence, emissions duration, dependence on facility type, etc..) using modern data science and research techniques. Opportunities to present work in scientific papers and conferences are possible. 

Duties:

• Develop statistical methods to use GHGSat emissions data to estimate emissions over different temporal and spatial scales 

• Incorporate emissions estimates from other sources such as bottom-up inventories and models. 

• Validate, improve, and integrate methods developed by others 

• Work collaboratively within the Science and Analytics teams and with other Subject Matter Experts across the organisation to design and prototype solutions for analytics problems 

• Present results (to technical and non-technical audiences) 

• Provide high attention to detail with ability to manage and resolve multiple priorities, project complexities and uncertainties 

• Keep abreast of the relevant scientific literature  

• Demonstrate strong communication skills and critical, bold thinking in all situations 

• In-depth experience with some or all of the following:

1. Emissions estimation using remote sensing measurements 
2. Energy system modeling 
3. Atmospheric modeling 
4. Data science (machine learning and statistical inference) 
5. Geospatial data processing 
• Proven experience as a research scientist developing rigorous methods to estimate physically meaningful insights from empirical data 

• Advanced degree in Remote Sensing, Statistics, Energy Systems Modeling, Physics, Computer Science, Data Science, Artificial Intelligence, or similar 

• Strong analytical and problem-solving skills with the ability to work collaboratively in a cross-functional team 

• Proven ability to deliver projects on time