Senior Data Scientist, Outage & Extreme Weather

This is a fully remote position, open to applicants in Colorado.

📋 Description

• Design, develop, and validate machine learning models that predict transmission outages caused by extreme weather conditions.

• Create spatio-temporal models that connect weather forecasts to the risk of infrastructure failure, including estimates of failure probabilities for transmission and distribution assets.

• Develop models that illustrate the relationships between transmission outages, extreme weather events, and the risk of wildfire ignitions.

• Combine weather model outputs, asset and infrastructure data, historical outage records, and geospatial layers into robust and reproducible modeling pipelines.

• Transform research-grade models into rapid, reliable production systems for real-time forecasting workflows.

• Assess and benchmark model performance against leading methods in the field.

• Convey accuracy, skill, and uncertainty to internal teams and utility customers.

• Collaborate with meteorologists, risk modelers, and software engineers to enhance outage and extreme weather products.

• Utilize AI agents to expedite model prototyping, pipeline development, testing, and documentation, while upholding rigorous review and validation standards.

⛳️ Requirements

• Proven experience in developing models for predicting transmission outages (a core requirement).

• Over 5 years of academic or industry experience applying statistical modeling and machine learning to grid reliability, storm outage prediction, or related issues in the energy sector.

• Experience collaborating with utilities, ISOs/RTOs, or grid operators on weather-related operational forecasting is highly valued.

• A solid track record of peer-reviewed publications, patents, or deployed production models in the areas of outage prediction, wildfire risk, or the impacts of extreme weather.

• Strong foundation in ensemble methods, neural networks, probabilistic models, and statistical modeling for spatio-temporal challenges.

• Experience integrating physics-based or mechanistic models with data-driven approaches for predicting infrastructure failures.

• Proficiency in geospatial data and tools, including GeoPandas, ArcGIS, or similar platforms.

• Familiarity with large multidimensional weather datasets.

• Advanced Python skills, including expertise in NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.

• Ability to produce clean, well-documented, production-quality code.

• Capability to optimize model runtime and computational workflows for real-time operational applications.

• Practical experience using agentic coding tools such as Claude Code, Cursor, Copilot agents, or similar tools as a key part of daily development processes.

• Proficient in structuring tasks for AI agents through clear specifications, problem decomposition, and contextual guidance.

• Strong judgment in reviewing and validating code generated by agents for scientific integrity.

• A Ph.D. in Environmental Engineering, Atmospheric Science, Civil Engineering, Statistics, Data Science, or a related quantitative discipline is strongly preferred.

• A Master's degree with considerable applied experience in weather-driven outage or infrastructure risk modeling will be considered.

• Experience with R, SQL, or Julia is advantageous.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements and a supportive work environment.

• Contribution to impactful projects that enhance community resilience.