Applied Physical Scientist
Project Canary, PBC, United States
Job Description
Project Canary is a SaaS-based data analytics company focused on environmental performance or the E in ESG for energy and additional business sectors. We are the leaders in assessing and scoring responsible operations and provide independent, measured emission profiles, including methane, via high fidelity continuous monitoring technology that helps companies take ESG action.
Formed as a Public Benefit Corporation (B-Corp rating score 107), Project Canary’s Denver-based team of technologists, engineers, and seasoned industry operators have earned recognition for their uncompromising standards and high-fidelity data. Project Canary’s mission is to fight climate change and put actionable insights starting with the energy sector. We ingest data from various sources, including our own proprietary environmental sensors/hardware, to calculate carbon emissions from different facilities in real-time via SaaS. The resulting independent data can inform the procurement of offsets in real-time using microtransactions, formulate a data-driven ESG strategy that investors now demand, improve operations by identifying problem areas in minutes, and bolster customer engagement through radical supply chain transparency.
Founded in 2019, Project Canary, PBC has quickly gained recognition as a major mover in the continuous monitoring space.
Here are some highlights from last year:
- Fundraise totaling $121M, Series A of $10M in 2021 and Series B of $111M in 2022
- Certified as a B-Corporation with a score of 107.6
- Recognized as Best for the World (top 5% of all B-Corps) in 2 out of 5 categories
- Governance (transparency and ethics)
- Workers (treatment of teammates and culture
- Headcount growth by 14X since 2021
If you enjoy a growth-stage environment, mission-driven work, we want to hear from you. The Applied Physical Scientist will be part of the Data and Analytics team responsible for research and development of advanced predictive modeling to diverse problems across the oil and gas, utilities, and waste management value chain. You are a team player who has a significant academic and industrial experience applying first principle-based models such as reduced order models and state of the art machine learning (Regression, Classification, Decision Trees, Random Forests) and deep learning techniques (CNN, RNN, LSTM, GRU).
Responsibilities:
- Support Data Science team through development of plume dispersion modeling to resolve complex fluid problems in an open field
- Build AI/ML model for emission detection, localization and quantification of pollutants based on data from emission monitoring sensors
- Participate in analyzing our sensor data and publishing the result for internal and external audience
- Assist the development of white papers for quantification analysis as well as additional technical and professional writing
- Perform data analysis and discover patterns in data using ML algorithms
- Engagement with various disciplines within the Project Canary team including science, software, and regulatory members
- Develop and support scientific projects that enhance our understanding of methane emission patterns and opportunities for enhanced methane mitigation from production and distribution of oil and gas globally
- Remain at the forefront of climate science, including staying up to date with scientific literature
Requirements
- Master’s degree or PhD in Mathematics, Computer Science or Electrical Engineering with 5+ years of experience in data science and data modeling using ML algorithm
- Strong background in data analytics
- Advance knowledge of Python programming language
- Working experience with building AI/ML models using Python
- Knowledge of C# and/or Java is preferred
- Demonstrated ability to apply proven methods to new applications
- Strong research-orientation and curiosity
- Experience in performing rigorous analysis with short deadlines in support of highly visible work Demonstrated scientific expertise, including but not limited to a record of scholarly publications and/or involvement in scientific panels
- Experience synthesizing, interpreting, and communicating scientific data in an advocacy setting and for non-scientific populations
Benefits
- Salary range: $130,000 - $150,000 annual base
- Hybrid work environment (3-days a week in the Denver office)
- Health, dental, and vision insurance with low deductibles and premiums paid by company 99% for self and 50% for dependents and/or spouse
- 401K with company match (no vesting period)
- Opportunity for equity ownership
- Student loan assistance
- Unl